{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 准备开发包\n",
    "* numpy：是用Python进行科学计算的基本软件包。\n",
    "* sklearn：为数据挖掘和数据分析提供的简单高效的工具。\n",
    "* matplotlib ：是一个用于在Python中绘制图表的库。\n",
    "* testCases：提供了一些测试示例来评估函数的正确性，参见下载的资料或者在底部查看它的代码。\n",
    "* planar_utils ：提供了在这个任务中使用的各种有用的功能，参见下载的资料或者在底部查看它的代码。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from testCases import *\n",
    "import sklearn\n",
    "import sklearn.datasets\n",
    "import sklearn.linear_model\n",
    "from planar_utils import plot_decision_boundary, sigmoid, load_planar_dataset, load_extra_datasets\n",
    "            \n",
    "#%matplotlib inline #如果你使用用的是Jupyter Notebook的话请取消注释。\n",
    "\n",
    "np.random.seed(1) #设置一个固定的随机种子，以保证接下来的步骤中我们的结果是一致的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 加载和查看数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, Y = load_planar_dataset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.scatter(X[0, :], X[1, :], c=Y, s=40, cmap=plt.cm.Spectral) #绘制散点图\n",
    "\n",
    "# 上一语句如出现问题，请使用下面的语句：\n",
    "plt.scatter(X[0, :], X[1, :], c=np.squeeze(Y), s=40, cmap=plt.cm.Spectral) #绘制散点图\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据看起来像一朵红色（y = 0）和一些蓝色（y = 1）的数据点的花朵的图案。 我们的目标是建立一个模型来适应这些数据。现在，我们已经有了以下的东西：\n",
    "\n",
    "* X：一个numpy的矩阵，包含了这些数据点的数值\n",
    "* Y：一个numpy的向量，对应着的是X的标签【0 | 1】（红色:0 ， 蓝色 :1）\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X的维度为: (2, 400)\n",
      "Y的维度为: (1, 400)\n",
      "数据集里面的数据有：400 个\n"
     ]
    }
   ],
   "source": [
    "shape_X = X.shape\n",
    "shape_Y = Y.shape\n",
    "m = Y.shape[1]  # 训练集里面的数量\n",
    "\n",
    "print (\"X的维度为: \" + str(shape_X))\n",
    "print (\"Y的维度为: \" + str(shape_Y))\n",
    "print (\"数据集里面的数据有：\" + str(m) + \" 个\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看简单的Logistic回归的分类效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\SpacialSoftware\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:578: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegressionCV(Cs=10, class_weight=None, cv=None, dual=False,\n",
       "           fit_intercept=True, intercept_scaling=1.0, max_iter=100,\n",
       "           multi_class='ovr', n_jobs=1, penalty='l2', random_state=None,\n",
       "           refit=True, scoring=None, solver='lbfgs', tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = sklearn.linear_model.LogisticRegressionCV()\n",
    "clf.fit(X.T,Y.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以把逻辑回归分类器的分类绘制出来："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "逻辑回归的准确性： 47 % (正确标记的数据点所占的百分比)\n"
     ]
    },
    {
     "data": {
      "image/png": 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n38SquG6gfr9GOKqRyzrksuU6ASQCsXj9TCIWNwgENFJJi1LZoZBv7FV0Mzb7IrFSimJBkc/ZlIoOpZLrBZVoN4gndGSVEWChsM7OPc1nZI6jFoPx7qi/jqtUIzEvlfRWwFMAHmuK47imgPmUa6ePxTQGd/tZcO1vJrDCEY1QWCOfcxaVgAgEgkK0gQIA8Pk1uvt8AOQyNqPX6xXISohAW8fm/QQcRzFyrUw+7zDdv5vrxw9T9gdJzE6y++IpOuezDOz0rVoJrMgaWm3u5jWVu43N+/Z7bDmUoxi+WrvYOpe0yWQcdu/1r5hOWEQY2OkjM+8WJFcK4gmdWHx1o9xwVGfXXj9zs5abhjqgYVcU2RVKHrZ3GoQjm3ekOjNZoVBwuHLoAUb33otjuCabyUCImd4dPPDjb9GezxMK3/k9aLobyFcqNs/uuhrlKuIVktlKeArAY83IZOwa4Q+u0LAqinTKoq3DbH4yrhKIxQ1i8dt7Lf0Bjd4B3+Lf6TmL3JIZxVLaOnTaOwymxsukU67CCUc0unrMuiI0rSKdsin5gozsu682N5KmYYvJpfseZvDi99dEAQD09vu4PlTCWaYzozGNzHxzRbpUP/f0mfh8m+P5edwcTwF4rBnZ+cbCVinIZhzaOja2P9G4zsy0VeeOquuu6We5a2g245DPldi9319XqawVOA6kO3rQHAd7uYwXcfddXjtzS6DqEjo3a1EsKEy/0N5hUCo6ZLNOwzUWn09IdLiL/ZGoXpcHymNz4ykAjzVDX+FtasViq6YJu/b6mZ6okMnYoCASdUf5paKiXG7sGpqcsejp8zVudANQwFiwm8snesmbIVQTE5hm2w0XyO8E03djXeXGNkHGK3XLBCKup1cs4YmRrYr3n/NYM+JtxqL9fimu10pr7MKG4SZK61u2PTVXbuo1tBbeMLeLAr7b8wTXQ71u4XsUNEimrdkWe2cubYi5StOEwV1+RodLboBdtaNt7XrTBXqPrYGnADzWjEBAo7PbYGaqNriqrcMgGNRIpywyadstWp4wCEe0tfFguQ0MQwMaxwC0MpDpSnjQFf7awnqJLHQKzbZxNA3NsYnn5vhI8eyG9SsY0tiz38982rlh7rnL02hsBzwF4LGmtHeaROMG2XlXuIajGoYhDA+VKBVvmFxymTLRuE5vv9kSJRCOajDReJ9tuUqgFf06F9u7RPgvQSliyUnaZiaIzU3Tk53E3B/YkD4ppZiZrDCXvFFvIDNv07/Dt+njKDxWpvUrXR53HaYptHUYtHUY+HzuyH+p8IeqEEnbNcVgNhLHpmkksVLNc+esN06zT1KEYD7LrkunaZudwNzA0ffcjMVc0jXtOY77fPI5Z7HAj8fWxVMAHutOJtXcOygz35pUDDcLVtJaZNq+J3sNw6nXPppt0TU2BGxsAJtSipkZq+H/r1hwKJe8tA9bGU8BeKw/m9BKYJpCIFj/+otAJNa6cof7M9cIWYWamseaVaF9ZoyO5Pii5816B7CVSg6z0xWGLhWbLpaLuOk8PLYu3hqAx7oTT+gUC/WzADfPT+tewf4dPkauubEACKAgGNTo7Vs5YG29UMCLPY+RMwKohVJeyiFu5fjYxGvo/T5CYW1dUy04jmLserkmJUfT/io3DsBj6+IpAI91J5bQmU/bFAo3golEIN6mNxyFbxSG4cYJlIqKSlnh80tLa9xe8/cwEurFXroILBoZX5iZvp3sz15f9z5MT1ZWJfzBjZw2vajfLY2nADzWHRFhcJePbMYhk7bRNFcpBEOtFx4iQiAoBIKt60Ox6DAxWua9QwMNPYAszeRiZNe6KwClFKnk6tdkegdaM1PyWDs8BeCxIYgI0ZhOdAukCXZsRSplkc86GIaQaDfWbaZiVRTnpvyM776P+USXa1dp4J4ka5muswm3WhvBq/y19fEUgEdLqZQdZmcsinkHwxTaO401S252O1iW4trlIrZ9I/vlfNqmq9eoK6CyFrxt7ub9px7CEXFdjxrYXgynwsHM0JpfeznJ2dUrAJ9PWhbE57F2eArAo2WUig7DV29knyyVFPlcma4e46aZQ9eLmckK1hIvzPl4B6nOXsasMo84E4S0tQsQyOpB3t/xEM7SJEpL8y6LYDgVBvMT7M6Nrtl1m2GVVzfLEIGuXs/8czfgKQCPljE1XqlLPawUTE9axBPGivUD1ouFuARHhA8eepZkVx9KNATFReBTUz9mZ75JCPEtMhQebLxDBL1SZmDuOoetEXYUJjbEk9YfkKZunZpW9frxC1095qauo+CxejwF4NESlFLk882DiPI5m0isBa9nVdKO7r6X2e7+xRSnqvrznZ4n+aWrf0agSR6hW8EWrWk4slku8fHkyQ2L+FWOair8TZ+wZ7/fM/nchbTeDcNj27JSKoaZaaslSdkWFqlH9t3XML+1Ep239L1rcq2d+bGGi7tiW+zLDm9ouofUnOXGQzSgp681+Zo81h9PAXi0BBFZsXB4qahIpzY+TURnt4lhCmWfv+kxo5He225fKYVyXEHbVslwaP4KhlNZ3K87FmGnyEP5C7d9jdthPlWfxnuBfK416To81h/PBOTRMnp6TbLzzQVPKlkh0baxr6hhuOYOn12mZDRY6BRBnFufmVTKDhPjFfLVGsXBkEZPv8mTs++yozDBB7H9lHQfe7Ij3Ju5gn+JUtgIvIQO2xNPAXi0DN0QRAPVZIDptGjgqWnCwcwQ7/vuq7dTOQ59s8NwCwXDbFtx7UoJe8n9FPIOw1dK7NkfYFd+nF358bXp/G0SS+jMTNYnfROBaCvWYjw2BM8E5NFSVrIs+1qYluGBzHl8lVKtX77j4C8VOO6M3FJb8ymrztsJwFEwl9zYkX4zEm0Gfr/U6DsRVzG0Ml2Hx/rSsv+siOwQkZdE5KyIfCAif7NVffFoHSsJl0Rb61wN/U6Fnx79C3Ykh9AsC82q0D95lb809AKxwK2lQC7k62sPA6DcfZsBTRN27vHT028SjmhEYzoDO330tCgxnsfG0Mq5nQX8ulLqHRGJAm+LyHeVUh+2sE8NuRzewVvth8kYYWJWjoeSp9m7AYE524HObpN8rlQnIA3DLT7iOKplKQciTpHPpN6E1Js3Nt5GrXjTJ4vZRpezkdk0rYpidrpCNuO4ZTnbdNrbDaT6fEUT4gmDuFfkfdvQshmAUmpcKfVO9fcMcBYYaFV/mnEmtp+Xux8h5YtjawZzvjgvdT/G2ejauAJudwJBjcFdPvz+WkFo2TA5VuHS+eIt56jZbCTa9Yamro0s7GJZiqErRVJzNpblZj+dnbK4PlxuaQ3kjUYB9k3EXkV0KrI9At02haoXkd3A/cAbDfZ9CfgSQI+5sSkbbTTebD+KpdU+JkszeKPjGAczV9Fu039iLNDFW+1HmDNjxCpZHpz7gJ2FtYkw3WqEwjq79+tk5i3Grldt4sq1kQOMDpfZeyCAsY558NcD5Sjm523mUxaGAZUl5n4RN5vmRqWfnput1CxCg7u8Ucw75LI2keimEAV3RE4PcDmyk5JmMlCYoq84vah4F77lD+P7sMQgZuV4bOZd9uTHFs9PmVFe6XqIyUAnAD3FWZ6aPonfKfNu4l6GwoMYyube+cscTl9CZ+tXQ2v5f11EIsBXgb+llJpfvl8p9RXgKwCHgokNHarMm+Gm0Uq26GSNEDErd8vtXgkP8FL3Y4uKpWgE+K7/SZ6YeYd7M1ebnpcyI7yXuJfJQAexSo4jqQuYysJUNu3l1GYsvHVLrJSKOJO2N2y0vBLlkkOm6roaiekEmghwx1EMXy1SKtbvE3FNP5Hoxo0ysxmnoQlKKRgfqbD3gL6lC7xfDg/yUvejKARHNN5ru5eQVeBjk6/TW5rlez2PcT3Uh1395ubNCN/veZyPT77Krvw4Bc3Hnw58nLJmQLUYz0Sggz8d+DiGcihpJk61TujJ9qMMh/r47PgrW/6ba+kXJSImrvD/PaXUn7SyL40IOOWmRbodEfzOrRfFVsCPOx9sOKt4veMEkUqet9uPkPTFCdt5Hpg7yz3Za5yL7OYH3Q+jEBAhZcYYDvWhKRsBfE6F58d/QFc5VdNuXg+ggLDdQBJtMiyrsX5XCiyr9aOtmakKySX1cZMzFrGE3jBSdi5ZoVR0/98TO/YzdPAEpUCIQCHL7nPv0jd2lXTKWpcMo41whXvj5+s4kJyp0NVzGwscm4C85ufFnsdvVFEDHHSyRpiv9T+H6VSo6L66wZw7kz/Orvw47yUOUdbM2mNEo6IZWFDTtqUZTAY6GAt0M1CcWu/bW1dapgDE/WL+LXBWKfVbrerHSgTtEr3FacaDXThLbIKaYzNYmLitYJ2cHqTUoOgHgCU63+5/avFlS+lxXup+hFc7jlPUA9T56AGOuP/Cguj8yeAn6S9Mcjx9gaBV4OXuR0mbUQBilSzPTr1BV3nulvu8UYTCGuVS/SxANAiG9EVbdSvSEhQLTo3wB1cxzadsIlG9bjSfqqZWvr7vCEMHj+NUg8qK4RgXjj+BbZgEpi/R1r4x/W9rNyjkmw9Y5tMOXT0b05fbIW1EeC9xyJ39WlmOp87TV5wBWBz51yHuYKki9cJ/gVT1+zgX29f4GGls5LXEYCTU4ymAO+BJ4BeB0yLyXnXbl5VS32phn+r42ORrfLP/GdJmpOrIISTK8zw79eZNz22EqSxUk5fRaZAcTIlG0VjF2kf1vLFQL5OBThzEVSTV7XP+ON8YeJYvDH9r084G2jtN5lN2jc+8CJimW6xk7HoZpVyvmu5ec0NNKOlUfZAUuEogPWfV9cVxwNZ0ri0R/ov7DJOr9z7I/uTl9exyDZGYRiAoFAuNZwGtMmVURCevBwnZBcwmEYHTvja+PvAstugo0ZjzxRkJ9nLv/GUiVp6RYHfzxFKw4r6AXWLeCFPRmojCJgV6AMYDneT0wKb9nlZDyxSAUupHtO69WzVBp8xfGXmBKX8HaTNKojJPVyl52x33OxUG8lOMhLpRSz0NVnjRbhVbMxq2Z6PxQXw/jyTPYInOULifvB6kq5QkUZ7nfHQPc74YXaU57sle2/B0BKbp1uidnqyQy1ZdFeM6+ZxTsz5QKbuFywd2+jYsLfFKUcmNgrxMv5Axog0LvAA4mobZHQM2RniICP2DPq5cLDXYB9H4xnq92Aivd5zgbGwvGgoH4d75yzw+e6rOseKHXQ/WlsoUwRaDM/EDaMpZtNnfKrpjcTR1npLuw1A2lUbtNPsmRZjyd/DHOz7FX73+AmG7cFt9aDWtX1XbAgjQU5qlpzS7Ju09O/0GX+t/jrwRxEZrOPK/Yxq052g6M742pn1tfLP/aRzRsHFz3TuioSkHWzO44li81X6Enxz9HolKdm37dRN8fo2BnTcSsc1MlSk1yFKpFEyMldl3YGM8wyIxnUzGXixqv4CIO7peTnePSWasuLhwWIem0R7YYAXr0+jsNpidvjGbEXFnVB2dGysKXus8wfnoXmzNWEysfSZ+gLFAN58ff5lAdX3NRmPG39a4EZEa0+wtoRT7stc5kT7vzixupwlNp6SEt9vu46mZt2+vHy3Gi/FuAUG7xBeuf5tPTvyYx5KnMJy1qzK1Eppj01ZO8+2+j1LS/VSqng22ZqBEW/SQsDSDkmbyUvejG9KvZiilSM40H3pbFTbMhz0S1QgE6lMlmD5pGDgVCuv0JyokZsaRZf6XmmOxOzeKfw1qCtwqHV0mO/b4iSd0IlGNnj6TXXv9a1p8x0EoaP6m/vYVMTgX3VvnCIEISX+Crw5+YtEPXxpb9+8YQ9k8NX0Sqf7+yOzp+u9wFe+WEo3z0T388eAneStxmKK2tRbSvRnAOmCJzligCwH6itMYDWybAgwWJhksTDIe6GIoPFDjabAqlg7jGu1btl3DoauU5Gx8/83bFnfkVdR8i6Oxjcaybv4NloqKQHD9LYkiwuAuP6k5azF1ciyu09ZuNI1Ubu/y8WjpAj8uR8n7wmg4OKLRXZrl6emT697nZgSDGsGB9RFUH0T38UbHMSwxUECikubBubPsyY2wMM7OGkE0VGP1J0JBD3AhupvD85fRUOzMjXEt3H/z70MpN7Og6CvOqDXH5qHkGZaO+4/OXyRs53mn7TBZI0SiPI8SYcbX1iHLOl8AACAASURBVHwWV8XRdGb9bSR9cc4k7uGvXP8LfMpiONSPLRqD+Qkim9RE5CmANeZyeJCXux9BqpJLifDM1JvsyzVPIPZo8n1Ggz1UqiPxhiyThIay6S1MUdHMxcCVhZfecCokyhmKus/1HsJd7Hpu6nVKmm9VI5vFyzYYfxU0H5cjO8nrAXpKs+zITzQNiCtXvZR86tZnOfomC8bUNKG9w6R9FfWK00aEb/U9Rd4IIEqhROgrTPPI7Pt0VOrCXe4KPozu5cddD9S8wyl/Gy/2PEa8kuWnRr+H36kQtgo4K4zrbc1gONTH4Xl3kfyjM28x6/84xeqstdl6WdAu8vz4D5g3I5yJ30PSl7gR0SvuXMLvlHkweYYj85fqzt+bG61J8VLUfPx5/zPM+hKLbayEEo2S5uP3d34WDVUt9uNe91jqHI/MnVnx/FbgKYA1ZM6M8lL3o4umlAVe7n6U9pE0bZVMw/PilSx/ZeQF3mm7j6uhAcrLfZaVImCXeHbydcZD3diisyc3Qm9xBsH1pLgW6udSdCcOGvdkr7E3ex0NxbwZQVWvIbjCe7V203glS9CpXTQcCXbzF70fdUPqRcdQFvFKhp8YfalGyCfNGC93P8Js1X7bWUryzNRJ2m5B+GmaEI3rZNKNTSWa5tax3WgKeZvkjEW5rAgGNdo7DXz+pT7owjf6nyFnBGsWKMeCPUwEu7asAsjpAT6I72fK30G8kuFI+uLiO62A1zuONx7AiMa8Gea1juM8M/0WPmVxMDPE2djehseLcghZNxbHQ3aJLwx/m6vhAab97eSNAFfDgzXfmeFYfGTmbbrKKbrKqboBl8KdmRvVuJnVEHDKPDV9kq/3P1f3TbuNNlBEIig07GXbTycO0luaZWeL034vx1MAa8gHsf3ugu4ybNH4YeeD7ChM0F+YwueUORfdR9YIMVCY5J7sNWJWjmemT/I0J3kncR/vtt2LplyTQWdpjk9OvkrILrKzOFnXvqls9ueusz93vW5ffNkibtApcyx1jtOJgzdssMoBBEGhRENTNppyeHqq1kxhicYLPR+psd1aYjJnxjnZfpQnZ98FIK/7+drAx2qiKqf8HfzRjk8jKEJWkcdm32vY3+X09plUyk6d+6II9O/wbXhMQHrOYnK8sjiJKpds5tM2O3b7CYbcex3xd1EUs847xdIMTiUOLY5stxJJX5yv9T+HJTqOpjOmurkQ3cMnJl9lZ34cWzR3dN4EJTqXI7t4ZvotAJ6YeYei7uNKeEedENWVw33LnpGOU/OOXwsN807bYebNCIlymoeSH6zoky/Q1M10JUqaH105t7Za0+CdtDSD0/F7PAVwN5Mxww1HNEo0JoJdTAS7FkcNCkA0rkR28OOuB3gg+QEnUufRcXgw9SHH0heY88UI2kWiVn5N+/nw3Bnay2lOJQ6RN4J0F2c5kLnKcKifOV+crlKSo+kLdWkuRoM9DR13HU3nQnT3ogL4MLqvWvB8ybOofhQKIWeGeLHncbKzQU6kVy59qOnCrr0B8nmbVNLCqkAwJCTaDEzfxvowOI5icqJSY0HLh6OUghHUbIqDIXfb2LyJ6m2smApVk9xW45Wuh2oiZZVoWKLx/e5H+aWhr6Evd49qgLNEMOooPjH5Gu/FZznZfgxRDiKg0Hhk9tRNAxY3qohOVymJvUaJ4Yp68zKjrcJTAGtIX2Ga0WBPw+niomJYLhdEcNB5u/0II6E+Pj/2EhoKU1l0l5Lr0k+BhjOGpYmxGmGJ0bR2oL1E2E8FOhpPmWs6IZzsOMbR9EVW44QXCumEQq1dFCgWncWszmWfnzMPP0c23oE4No6uM5Yd5smJk/imZuBAk4XhUqrh9s1MRXSm/e2NXYurzgLdpSTdxRmmAp1NnBIcBvL1s9cT6QsczF5jONQHwM78OEG7PlahVQScMsdS5zmdOFAz89Udi/vSlzidOLgqF27NsdmxyUb/4LmBrin3Zq7gcyxqnMVXueCqRGPWn1j8EDYj/cWphiYulMNg4cbH3VaeR1vFdNtBY96MrGUX1xVtYeYGnHn4OTJtnTiGge3zo3SDy9GdvNV+hEg2RXx2As2uXfjWLIuHJt+rb3gTYKMx7W9jJNDNybYjvNT1MBciu7BW4Zm24PDwyckfoyu7/p1XDj7H4onZxvcetEsczAxxMDO0qYT/Ag/PneYj02+TKM/js8v05yf53NjLPJE85bqSOkvuWTmgFNqSyEFRDj6nwtH0xdbcwAp4M4A1xO9U+KnR7/Jqx/0Mh/tRLAyYV2enrmgmQ+EBduQnuBoeYCzYTdgqcDBzdVO4kQXtEvenPuS9xL2LoyFRNqZj89jsqcXjDs9f4sP4fpxV3HYjF1NLdK6EdzDjj5OoZNmXHd7wqORG+AOCrsF8MEY23oFa5h5oawbnOg7wpDrJkZMvcfXQ/YztPoijG4QzKe758E0GO+fWPujvDjkb3ctrnSduBCUCiHAlsoO32w/zUyPfo7c4w0Sgs87EaTgWnVVzTdgu8fPD3+Tttvu4HNmBLTo+u8ye3CgnUuc2xTt8OwhwMDvEwexQ3b57M1fpLKV4r+0QSV+cjlKKI+mLDIf73EA30didG+Xh5JlNqdxkKxWDOBRMqN/Z/5FWd2PVJH1xvjrwcZybmUMWUA73zl9mPNhD1ghiaSaaY6Oh+Njka+y+iYlmo7gW6uP9+EHyRpD+wiQnUufq1ilGgt18v/txKprumo6WC72qZ9MvX/tazeaMEeLPqml5Lc3EcCpoSvH5sZfoLLfefFIsOJzKtHP6oWewzXqbriiHn3zzD0lNuVXOFgYAmii6egzaVuFCupFcD/bwQu9H6oOyqmiOzYHMECdS5/jTwY9ji46lGYvv5fPjP6C/OL3Bvd54FJA1QiiEqJXb/DlslvHkmW++rZR6aPl2bwawjrSX07SV511XyFWM+ty84z7mjfBi8ImjuWUnXux5jF8a+tpteTKsNatZgBssTPGL177GrC/BhchOTicOuTtEQLk+0p8Zf6XuvJe7Hqag+xdHmlbV7/tr/c/xhevfvqVRpG0pikUHTZdqFO+df7aBoMZ9wQLv640/naBdpLNDMDWD5LSFZYFhQmeXSbxt831u77bd11T4g/v+XY7s4OmZt/i54W9yLrqHKX8HiUrGTca2RUf1t8K0v40Xux8ja7ir/CG7yHPVOgNbnc33Rt5l9BZnmA2sIuevUuiOxZXIzobKQhSMBHvZk986tYgF6Cyn6Ey6ftkn24+QNcL0FKZ5NHma0LIYg7IYTAS76j2pRLA0gz/e8Sl++vq3mQh0U9AD9JRm6CrVe4sopZiZrDCXtBf0DYYhDO7y1fjr3y5RStyTvcalyM7axW6laC/MUdb9tLXLhuX6vxNWswaz8P/wOxWO38RraytiicbZ2D7OR/fgIBzIXOPw/EVMZZPXA3yj/9kaF9eMFuGb/U/zM9e/s+YeehuNpwDWmd7SDOedPbXZDJtQMlZ2EbRXsSC3WekpJfnc+A9WPKbhAvMCIlTE4D/u/Bx6NXukAD3FGZ4f/2FNeb50ymIu6aZrWLBwViqK4aES+w4E1mQm8NT0W0g2x/new2567+rPaKiH/zT4SX565IWWpdC4FdpLKXJ6sPkMVTnszG0O0+N64CD8af/HSfrji27Lb5pRLkR38ZdHv8uH0b0No5YdNM7E9vN48v2N7vKa4imAdWZPdpSTbUfJGtrKOUVuIpQc0Wo8be5GAk6ZWCVLyhdvuH/RLLZk23igkz8Z/DgFPYChLO5LXyZy6f2Gzle2BdeHynT3mU1LOa4WZTuErgxD9yHXxrOwXTfIazp/tOPTPDZ7inuy19bEXmzbiuRMhfm0e/exuEZ7p3nHZRwfmvuAkVBv45RrSuFzKjyWPFW/7y7h/fgBkv5EzfenNJ2UL8alyC6S/kRDl2ZH093ztjhbd0i5RdBx+KnR77E/ew3dqWY3Wx40s9JCvFIYjsXDydNbYkR5pzw9/RZSdaWro8E2RzNI+hIUjCAZM8obHcd58RO/wKlHP04mVm96K+Qdhq+UyGbubC0ln3OY7R5ANVoLEKFgBPlh10P8qPOBO7oOVOsLXykxN2tjVRRWRTE3azN8pYTj3JkTR3cpybOTr9c/c+XQVUzys8Pf3vJmjpU41cSP383yuYuOUsr9bpehOTYdWzCmYzneDGADCDhlnp0+ybPTJ3EQftT5ABeie9CVTUX0aoWw+pfQcCoM5ic5mr6wLTwtwF0z+fT4D/hO31OrTwS8PEezCHPdA7zT0cP9P/o2sfnagDqlYGK0zL6Dt28OEgHDqiCOg2qStc7SDM5H93I8db4uqvpWmE/bVCqqrhxlpaLIpO07Xly+J3edgWtTvJu4l9FgDwGnzJH0RfbkRract8vNsNGwNB2fU0GAUrPoXKVwROfezGVOtR2qSwWh4XBkE/r13yqeAthgNBRPzbzNw8nTzPni6I7FNwaeq7PvG47FkzPvcihztUU9bR07C5M8N/k6r3Q/4mZUVO76h0KaltOsQwSlG7zz9Ofov3qefWffQl+Sl9+2IZ+zCQQ1dP3WJ8KhsEbX0BBXD96/Yhyz4DAW7CZ2B//HbMZuOiHKZO5cAYCbcO3JJoFaW5GK6FwL91PSfPQVpolaeX7UeT+XI7tQIgStAk/MvovpWG7yxQbszo0Sskv8xOj3ebHnMTJGBFBErDzPTr1xV3hAeQqgRQSdMsHqqP65qdf5fvdjCO6ilIZid26Eg9tQ+C+wP3ednUPjjIR6cRAGC5O83XaYc7ElhURuVkazOrOa2HUPuViC+1/9i5rdI9fc4DLDhB27/LfkIaRpQtTKs//917l07DF3faKR9xZg3mEQm7HEzl8MhJge2IOlG7RPjxFT65MuZCszFujiO30fBXUj/5DpWJSrBZAAcmaY73c/xu7sCFeiO+s8z3Rlcyx1HnA92b5w/Ttkdbf6XNgu3DUzI08BbAL25kbpv/YNroQHsTSDgcIkHeX0qs+/GhrgzY6jzJsRwlaB++c+XJw5XA/1MhboJuCUuCczvKVql/qUxd4laX2fmH2XjnKK9xMHKWh+wnaelBm7ad4hRzfIJDqZj3cQS9f7blsVuHqpxN57/KtOMKeUolJR9F+/RPv0GOePP0Gqq68uOhi45QyQSilKJYW2UHGszWA+bTM+sI8Lxx93I8w1nev7jzCdn+T56Veb1mPYblRE5zt9H63LTGo3KBJjawYpf4zB/ARjwW4c0RCl0JXN58derstRdTeM+JfjKYBNQsApc1/myi2fdyGyix92PbQ4Ks6YEV7tfICMEWY01EPSF8fSTHTH5q22Izw39XpN0YuthACHMlcXlZvCzVJ5MbLLrXGwonlIyCYaK4AFhi6X2HOPH8O4NZNQoJjn6Mnv8/6jH2e+rQtHc/POI8InJ358S8F782mLybGKK3oUGKYwsMNHqD/KheOP4yxZdHYMk4lIL2dLe7dkiun14P34AaxG2TubvBtpM8ZfHfkuM74Ek4EOgnaRXbnxGrfircKXP/s3mu88882Gmz0FsIVZKMKxPJLT0gzea7sXUc5iGgq7OjJ9sfsxBq59fVPk1rlTBHhm+i1OpM5zNrqHD+P7G6edADRxaNNWHsE5Dly5UKJ3wCQWX/nTEBGiMZ3MvCvcNcfh+GsvMN/WxXxXLwPtNntzI7f0nPM5m/GR2uMrZTd+ofDwgYYyzNIMPozt8xQAbsTuO+2Hb6m0ashy34nOcmpTpBpZyhOnf513Zq7yt/9Z77pdw1MAW5ii7ndLPDZAIagmaamHQv0czF6r2zfrS/BG+1Emgl347AqH0xc5nj6/6c0LiUqGx5Pv80jyDK91HONsbH9tzIVyMJXN0eAM9YUAa3E9hCoYhhAKr5x+uqfPpFh0sCyFckATaEtPc6xtnkDm1mYRjqMYHW7s5uvYkCvrTQPlVkrlsJ14o/0YTjPP9gb1sw3H4oHUhxvQM5cTz7vupKHf/Ds883dXYU76uwVg/YQ/eApgS2M61uq9YqoohMlAZ50CmPXF+bOB5xZH0BXN5J32w8wE2vjE5Gtr2e11Q8fhydn3MJXN6fhBdGXjiBC0Szw//gN0gWhcI5NeeXqvFMxMWezcs7IC0A1hz34/2YxDsWBj+jRiMR3tNoKz5tM2zgrd6pgdRe8/UpeeWXNsdme3pklvgZJmciGym+lAG4lyhkOZq4Ts4s1PXMZUoKNJLQKFpmzilRzzZnix0t7x1DkOZIbu/AaAP/zXP8+pr68yMGw1wn+D8BTAFsZQNtFKlnlfrH7nQhKcBjVLU2a07vA324+5ttMlx1uawbVQP3NmjILu52xsLyXNx+7cKPdkr22KxHTLEeDR5GmOpc4z7W8n4JTpKiUXvTb6BnyUSkXKN5Ev5dLqbMALpqBwRCMzbzM5XkE3INFm3NSryLYUqbkKVkWRz688y+q1UuzOjTAUHlhMK6I5NgGnzInUuVX1dTOSNiP86cCNLKO6Y/Fe2718ZuyVW062FrBLDctSCoonZ97jvsxl0maEgh6gvZSqqWG9nCdO/zrA6kbqAF+/pa5uGjwFsMU5kTrHD7seqrd7Vuv8NkIamHQmAp11NWyptvB6xzHGgj3u6FM0xoNdnE4c5KdGvrviR9RKgk6ZnYWJuu0iwp59QWamysxON1dgpk8olxzSc25Gz1BEIxrT0bT6Z2rbimtXSlhLgrVSSZuefpN4ovEnNjVRYm52tUoGIjGd56be4GJkNx/E91HWTPbkRjmaOk9wi0WIOwgpXwzTqfBS1yOUtBv1k23NwAa+1/M4Xxz+81tytzyausCbHcdqTWJK4bfLHMxc4cTzFp/Rfml1jW2iUfp64imALc6BzDXeS9xLxgjdcEGs2rwdBFtq/8WGU+FAA/u/3yk3CYhRjAR7a2zqlmaSMYRTiYM8PPfBWt7OhtHZ7SMWt7l2pVxnehGBYEhj6LKb078UCGEpH7GZDHv21OffmZmqUKksJv8H3MnX5FiFSFSvO358tMh8avXrKn2D5qLiOZAd4kCDwiRbhcvhQX7Y9RCOaDho1drR9WK+pPuY88VpX4U79B/+658H4NTX4rRP5AjPV7PMirvmdWVPD//gyK+t6X3cLXgKYIuzkGvo9Y7jXI7swEFjR2GCx2fe5fWO44yEehdNBoZj0V5Osz8zXNfOkfRFTrYfrVtQVA3nC+5I7VJ015ZVAAA+v87u/X7GrpcpFRWIO+Pp6NKZmbIp+oJ8+NDTZBKdSFVLTF97l8cZqmknnbIb1kpWQC5r13gUFYv2qoW/CMTbdKKxzfWZzhthTiUOMhnoJF7Jcix1jp5V1K+eCHTycvejdSP0RhgBjd/+6BeoBFZx7wvmF4FkX4R0RxB/0cLRhWLIvIl78PZmc71ZHrdFwCnzzPRJnpk+WbP9k5OvciW8g3OxPTho3JO9xj2Zaw19nI+kLzLtb+NqeBCpZuHRlMOBzFU+jO2vy4UCNC0Qv0BZDCxNJ2iXNm3kpGlq7NoboFJ2sB3w+4RMxkaJzXtPfppCKAqaBtUJ0JndD9AzU6mJpVie2+/Gjnr5lpq9+bpJLKGhiRBLGARDmytf44wvwdcHnsMS3a1j7YszHOrjo9NvNZxZLuX3D3yaYK5S+y40Ec45S6fiX3kRvhm2Tyfvu71ztxueAriLEWBf7jr7ctdveqyG4mNTb5A2P2A80EXALrEjP0HeCPBh7J6643XH4kCTVBV53c+3ez/KjL8NEHxOmaem32LfkqjezYbp01hcPlSQau+lHAi5wn8JjmHydtvhRQVws8ViX8TkYmQnWSNER3kOsVYWkv6A0DfQJEHZJuAHXQ/VLrSKhiUaL/Y9xr/b/xnXF7YJ/ZfnVjUQUECyO+yN3DcATwF41BCvZIlXsot/R608D86d4e22wziioUTDcCru1L9BdSgH4Q93PE9Z8y1+wGXdz/d6nsAce4WdxZVrGswbYUZCvRiOza78aEsC1kIRnYIRbTrBcZOCuVQqCtEazwKy0QR/uP95HNGwxI0ODsaPc/SVb2FWGi/c9g40juvYKB7/nWMAPPvVBrW3HcXOC8mmrgX+okUp1LzwUdmvY1QalVeppxBt7XPYLngKwOOm3J86x2BhkrPRqhtofpS92ZGGpqTz0d01wn8pP+x6kC9e/1bDayjgtY4TfBjbz8LKww94kGen3licOZTFoGAECFt5jKZ2lzvHMIR+I0uzZL+JSgaAQt4mOVtpKPwVcObRj7mBetVnURENOxDl4vHHuO+t+upog7vurFCNwi3xaKORqGRqAvhWTBOwlK+usG8lya3UTWNS5jtDBHNpZOli+bJmFVCImKjbyNDqcet4CsBjVXSV5ugqvX3T466FBhrvECFnhpueNxQe4Gxs72LKigVe6n6UzutJ3mk/wuXwTgTXvfVY6hwPzX2wKDwU8GFsH6cSBynqAbqKSR5Jvr+qxclG3BNI8V4lQ0qL1yR4MxyLh+ZOM5esMD1hNa3lk4u3Y/kDdYrQ0XRmencRiunkM+7icSis0TvgwzQbC9BZM0bajNJfmMKnLIZDvZT/2vPoGvz+e0I+bBKeL9M2nUeqBWKULsz2RShE1nAkLUIhYhLMVup0gaML5cDKdvdywGB6IErHRA7NdhAFqhqustBgxa8z23fzOsUea4OnADzWlKDTPMJKW2HUfjp+oEndZOGF3o+SNiNV5eAKmfcThzAcm/vTbhDUjzsf4Hx0z6KHyViohz8PPMtnx1+htzhT0+LV0ACnEgfJG0H6ClM8MHeWlC/KqfgBClqAwcIkJ9Ln+YmJV3i562Guh/pQImjKYc/0Jcwrw0xVF3MzsXamBvZQCEexqqUh26fHiKSTKEctLh4vxRGN7z75MwSsAoYoAqrCp/Zc4lh0iMj/8RuLwUd6yaLvWhqt0WP7Ts71WAI6a55WFVvROZphYld8dZ40qyTZE6G3mEKzFZoCp3rB6YHoqmz2xYiP0X0muuWgNMHRBH/BwqjYVHw65UDjXE4e68OKb4aIxIAupdTlZduPKaXuuBqyiHwa+G3cz+TfKKX+6Z226dFa7k9+wLno3vodSrEvW+9+ukCznEa2aMz5YnWBbgsJ746nzpLXg5yL1s8eLM3g1Y4T/OXR7y1uO9l2mPcThxYVRdYIcSmyy60AVc20mTajnI/u5rMXv0Po4lXUsV4UruvrlfZ9jB3p5v4ffYvhe44ysvcwzrKKYKmufveXZrkdRKiYfirGDfPQ70x2868yTzP9d/KLUdz9Q665ZCVxqFFvRlm8jIJYssBsf33k9+1imxqje9sIZ8r4ihaWqZGL+3FuxWQjgm3eeGalkEmJ5msHHutHUwUgIj8D/HNgSkRM4FeUUgt+hv8OuKNipyKiA/8S+AQwApwUka8rpTYuO5PHmhOzCzyYPMPb7UfcDVVhFrVyfHTmnabn7ciPkzKjtUnccAtzCNTlwAE39/vZCzZzXVEYtKFBLn7XE8mloPs5lbi3RlEo0VCoGu8VpetUHOGHiRPMLav7a5sm+UiMS0cfYap/L46xwhhK09xMbosBestScyz5XVMQyFcI5CoUIz7C6dJNhf9iMytsN0s24jgcevtdDr3zLppjc/XeQ5x68gls8zaFribk4n5y8c3rreSxOlaaAXwZeFApNS4ijwC/KyJfVkr9Cat7L2/GI8AlpdQVABH5A+AvAZ4C2OI8lPqQfbnrnI4foKD72Z8ZZk9+dMWsokdT5zgb2UMZWXS91B2LtlKaOX/jJFu6baFbFcxSqWm7hnXDi2g80IWmHOzldplGJgdNI9k1gNbAjKN0g6mBvXXKqg4RUEJ0bppMovOmpg1NQShTphjx4SveeYoNBZQDOp/7979L2/TM4kd75M23OHDqNP/p176E7fO8bbYzKykAXSk1DqCUelNEngX+XEQGuWkI0KoYAJY6qI8Ajy4/SES+BHwJoMcMrsFlPTaCtkqGp2bqF41LRYfkrEWpaKMbGvGETjSmkx7O8uClr3P1wAlme3eg2TZ9wxd40rrIq7ufYDjUV1P5S7Mq7Lh4BgHiyUl0q4Jt1EZ9arZF7/AF/vEzv0wxHCaQLdM1lmlsU2+Appymni3NSkAuR5Si79oF8pE4trmysFW4i6IApaBBNNVcsa0GBcRmx2qEP7ijN1+pxKPf+z6vfubTi9vbJqd45MWX6B4dxdF1Lh++l7efeZqK3xvp362spAAyIrJvwf5fnQk8A/wZcHgNrt3o66lTLEqprwBfATgUTGzuxPQeqKpbjDQQjtmMvSznvUM+6zCpVXAc8JPn0KlX4dSNI5IhjedCb/CDrge5mtiFoSsqBYfByx+y89Jp91rA8de/y3uPfxJHN6pCW0jMjDNw6QPOPHKEYjhMMWxWY5yXvUYNsqaKbdE1cpmpnfVBcE1dfxogykG3LXpGLjO262BdYFlNs8KiWSUf86MmcrDcDLS8rwt9UWqxbQU4GkwPxnjuq3/ReH0A2HXhwqICiM0mef4//gFmxZ0xaZbFvjMf0jk+wZ//8i/eVNmJ47D7w7MceP80sbkUhXCIcw8+wKUjh71F3U3MSgrg1wBNRO5bsMsrpTLVhdufXYNrjwA7lvw9CIytQbseLaBctBkZLlOVH+gG9A/6FouqKKUYH21S8MRpvpCZKWv8w8/8FwCI7aBbik///u/RMTVdc1w4k+Lx7/4n5rr6KfuDRFMzRDIpKqbJfFvVhCTC9GCU7uvz7p9VN8RAPovlD7ojcN1AsyoEs/N0Tl7FVykzsvc+d4G4WYrtm9AxcZ22qVFSHb3kozf6slSRKIFMIkg5aC7uH92boG8ojW4vHKcIZucpB8M4uo5mW7RNj9F9/RLnH3iMsi+KrQuZtoCrSEQQd4WjySLxjesfe+11dKvW7GTYNrG5FP1D1xjbs7vp/UVSKZ7/vd8nmMu77QKhXI5HXvgevUPX+NHnP3tLz8tj42iqAJRSpwBEaw6d9wAAIABJREFU5IyI/C7/f3vvHR3Xded5fu57r3IVUMgAEZijSFGBlKhAyZZsSZZlS05ty6Ht7p5ue7fnzPTZ7TO7PX32j92z//R6zvT07swG73hOb7ftcTu2nGQlS7SoQFJiFKOYkIgMFCqH997dPx5QRKGqQJAAqgDifnRIEVWvXt16hXd/9/7C9wf/G+Cd+v8e4B8X+N5HgM1CiPVAP45R+fICz6moAmbO5sqlwsndMqG3O8vPv/F1ok2N1A8O8eTFf8Jt3Vxlb9Z73f0gdQ1ThzN797Dv5Vfzq9VpNClpGL6u0ZMzDI4/9EBBoDbjd9G3ycli0U2bjM8A28NDv30FW/eT9vioiYxwecdGXvzKl3jsZ7/AH40Qr5tKtpzv5C8lUkDdyGUiTQ2kfT7ufvPXRJraGOjaQtrrx5tKADYD67oYb6tzUiBnYLt0+jfXo+UsDNMm69G5+82z3PvmUXTLQpOSnMvFWEsz3dvbi7KRAC7s3kXjQLEstgSurV2b/7m5/xpaiZ2NkcvRODA4pwF47Gf/jC+RLDIyLstiw9lzDHZ1cnH3nXNcLEW1mE+C8P3A3wBvAyHg+8BDC31jKaUphPiXwEs4Ybb/IqVcudKStxHZjNPm0OPV8lLG0+3sAJ7W/lXB8fe/9ApbOVk0AUgJD770Cr/96vPYulZQAVqK2StV0zA4e8/dRcdd3rGd2rExdhx+DyElmpQFBWEAiZoQxx5+iMs7i72VUteIh70zHnHz2hc+gy8ex5NOE62rw9Z1Nhy/wIe7HnEm/Zt1YwjH1XT00QdAe5Dn/t/v4rJMmgZ7aRq8HvqydJ0z+75ZNPnPxHbpZKfSJo89up/ezZvYdOoDjFyO7q2b6du4EVnGtXRx1y52vXuYUGSy4BpZus67T3wsf1wiFCQ0WSy9bLpcJIPlC/hqx8YKzl10GYB9r7zGZEMDbT09tF3tJhkMcu7euxlpL1M0qKgY8zEAOSAF+HB2AFekXJw6fCnlb4DS2gCKJUdKSWzS4rI3CAMZxpqaCCTihCKT2LqGbuYY7GhncG0X3x5dz0Rzc8nztPX0lPUz148MAxBpbCTj9Rat2qexDJ2c4UK3bYSUCCnp2byJ0/ftLXFiwbFH9nNm7x6a+q/RdG2ANVeu4M5k6N68mVMP7rulwGUqGCQVDIKUtF6JYHnq5zfxl3ELabaNbkuktKmJFE+uE42t9Gy8g+aeGJMNknidd1759KNr2hhd0zavz4QQ/POf/BF3HXyLLSdOodkW/evXc/ixj5IOXq+4PX3fXhqGhnDlCt1AUgiubt1a9vTudBp7jrgGOPGBJ/7pxyDAMC1soOvDi8Rra3BnssTCYU4+uG/OXYZiaZiPATgCvADsxSk8/H+EEJ+XUn5+SUemuGXKtbPzJpLcdfAgay98CAjiNTWEx8bxmRMAtHc7SpUCYGoeWNPdQ1t3D7vffperW7fw1tNPFU12qWCAmolISSOQm858EYIDz36KJ374IwzTLFzp6zpDHR289vnP0tbdgzeZZGRNG7G6uhJnvE7G56Nv00b6Nm3k2CMlxMtuBSlp7o7izljzm/xtq2QnNXAmPkt3AtKWrmPM8LFf3XwnPZt3YesGmhTUjqWoGU/hSQ9iuXT6NqzHXKTsG6nrHHv0EY49+kjZY/o2beTkvn3sfuedfHqrreu89rnnMD3ls5cmmprR5mpmjFOsJiwr/51rgGZZ1I5P5OMFH/35Cxx+/KN8qFxFFWU+BuBPpJTvTf17EHhWCPG1JRyTYhbT7pfZrpeylGhn58pkeOYf/hFvIok+dcN6Uqmi9MDZiKk/mmmy9sKHXFu3jit3bC845ugj+/nE939Y9FoJnL7/+gp+dE0bP/3Wn7L74DusO38ebypFzu3mwl27Ofbwg0hNq+oq0MhaNPVO4srJsi6NPFM+fnc2QsPQGEPt65GGq+D5mrFBEK0AXLhzF1tOnMSwLDIeH91bdiNn+Ow1CVg2DQNRJxMKSPl9HHn8Ma5u37a4H7QMHzxwPxfuupPm/mvk3G6GO9rLupamMd0ujj38IHcdfAuXWbrXQdkg9Ix/G6bJntcPcOmOHXMX1ykWlRte6RmT/8zHFhoAVuBI7/5FzqmYPfGL0sVOi4Gey3Hv62/gmTH5w81X87lyObYdO1ZkAEba2zl1/33sOnS44PH+9Ws5s+fegscyfj+Hn3icw088fpPvvrQYGYu2q5H5Vd9KSSLkZqIlyP5fvkXnpUtMNK0ho8/QsRGCSHM7nmSOjN/F+x95hJqJCVp7+xhp60JIGzm7wkzTGGvtQkwZAH8yxSO//DVbjp/g1S98riITY3ZqV3UznLlvL4naWu48+BZ1Y4743q0mfoZHxxhvbSl63KlmPsq2Y8dxZbIMrF3L8f0P3nCXqJgbZWoXkbs+YeL7gqOQUVJPfTZzSe8uEl3nzvPwiy+hm2bJLI+bpVzV7bFH93N6773cceR9dNPkwu5dRBsbSx67HAmPJG48+U9dv9FWP4k6PwAt/f0kQnXk3MXKnwiN8EiSobW12IbBa1/4HOHRUcLDUWzNKPleswXzBNDa28eX/vf/xOm9ezj1wP3LcoXcvXUL3Vu3UDs2xqO/+BWhiQmk0Mi53Yw1N7Omu7tg8VEKzbbLxm4efeGXrLlyFdeUG23d+fN0XL7Mr77+NWJ1S7d4ut1Zfr9Jy5RF0VNfQtypFPe//CprP7yIZtuYLhfndt/J9uMnCnzPC8HUdXo2lyiMmiLr93Ps0f2L8l6LjpSER0fxJlOMtzST9XoLnvYlzTknf6e4SnBtQx2267pbJOvxEK9poFxxvDtT6BaJNDYSraun/eJEUVaUmCoYm40AXKbJzsOHae3t5aXnv7hsi6smGxr4xR99nUA0im6aROvqcKfTfPJ7P8AXT+DK5aYEvQuNrS0E0bq6kpN53dAw7VeuFvwea1Ji5HLsfuttDj7z9JJ/rtuVVWsAvK9/FoD/7t+1VnkkC8eTTPKZ73wXdzabv6lcuRw737uxfn8pZs5L0+ezNI2s18vZPQvSAKwKgclJHv/JzwlGJ5GahmZanNlzrxM4nppIbU04uj8lkEDWrTG4rraokvfMvfew4fSHBUVVM7H04ona1jXGWgM0DF7fdehmDm8yxtrzJ4pPMoVh2TQMDdPS28dQV2fZ45YDiZqa/L+zPh8v/NHXWXf+Am1Xu8l4PXRdvIQnmUK3LCzDwHS7eP0zny55rtbevpLV15qUtHWXV5hV3JjbxgBMu1/+Irdzfv70f7f0Y6oUu945VDD5T3OjFW255y1d57XPPkft+DhbT5xy8s23bOaD+/eS8fsXZ9CVQkqe/OGPCERjBS6w7UePEgvX5guUYmEPtWMpJxg78+VA2qcz3Flbst9t38YN7Hn9gKNFpBsFBkICk/XeotcAJGu9ZH0uApNpPKksu98+REvvJfQbuOn0XI7m/v5lbwBmYxsGl+/YweU7dgDw/kc/wpqr3dSOjhEP19K7cUNBUHwmGa/HSTW1ioPM2XlmSum5HK29fUhgqLPj1pVQbzNWlAHoDzfN7YqpkvtlSSmTY143PEJzfz9pn4/1586VncxLTfSWpjHY2UFzfz+6aeU15QGidWEOfvITjK5Zw+D6dZy/d+Wt+GfS2tOLJ5Uqin+4cia7Dh3OG4Bogw9PysSbzDkSEVPHjbcESNSVnsQBdh4+gkCy4ez7nLt7tvtLEohlSdSVFjE03TqTTQEgwDs1H2Hva5LOS44LqKxxNgwyvlnnk5KmawOEIhEiDQ0lg6jLDalp9G9YT/+G9Tc8tmfzZva98lrR4znD4Oy9xYWCwrZp6e3Dm0ig2TaN1wbYcuJk/nfA1jQOfuJJerZtRTdNcu7SLUxXAyvKAKwmNnxwmrvffItgLEbG48HSddzpNMmaEFm3h/DYGOC4E1zZueUVbJzca3B8rVmvh98/+ym8iQQ7Dx2mcXCIaF0dp+/by0j7mqX9YBUmEIuVrUD2JRLXfxCCkc4a3CkTTyqHrWskg25kCRfOTNaev4Bu2/Sv314sKIfT7cqVMcl55r7V4uFaXv/cc2Db7Hv5VTZ9cBrNLmygnvH6ybpcXN1yPQ7jjcf55D/+AH88DjiFWxPNTbz8xS/cNiqepsfN7z77LI/97AUk04FyQe/mTVy4a3fBsQ0Dgzz+05/hymTRZ+wYZl5H3bZ55NcvYr/4EgDJYJAjj3+U3s2blv7DLDOUAViGbDl2nD1vHMhXZXpmZN7URCYLV/VTv+TlXDoS6Nmymc5LlwFJ34YNHHn8o2S9XrJeL28//Yml+yDLgPHm5rLqnZGG4iylrM8g65vfbdF1/gKelFNzkagpn47oTls3NAB5NI13n3qCQx97jPte/R2bPjhNorae87sfIhWowdY1mvvTROsgWu/jmX/4Hv544vp3LyUNg0M8/KvfcODZT9Fx+QrehFNYN9FSupJ7JTC4di0/+vNv0XnxEu5MhsHOTiYbGwqO0XM5Pv6jnxTcL3MxnZUUikZ55Je/5rXPPcfgDH2k1YAyAMsMYdvc8+ZbRSX5BceUeGx24Hb65zee+zS9W8pn7tzuTDQ3MdK+hua+fowZK0LTMDi6wIylu998K7+zcmVSZPzFrRcN08Q0bqJd4hTSMDj01BOc3nc/DQNZpBA4/4FuScKjKcKjSbKeEIF4ouC1Aui8dJmv/vu/A5xdn9Q0Btd28fpnni0pGrcSMN1uruzYXvb5rgsXb1iVPM3se8gwTe75/UF+87XVZQBu/jdTsaR4E8kiWd75YBkG53ffyXhTE/FggKtbNvOjP//Wqp78ATTL5tDHnub4Q48z2tyOJQSTdWHeePZTDK7tWtC5Z4qndX34AZo5yxVn27gyaQLR8Vt+D2G7sTVtauqf8TiOi+mD+x/PN6Mvfn4qw0hKDMuitaeXO99+55bHstzxJ+JoJQLF86V27Na/p5WK2gEsM7Jez001HJlGIDmzdw+xelUZOY03kaOpz9H+j4XXcPKBNeQ8OkNdtcgSGT03SzJ4XUFzTfd5UoEQ19ZvQ9gWUmh4Ugm2v3+AE/v3Md52a4FZV8YqykyaiQRG1qyjrefDG57LME22Hj/J8f2LpJu0zBhtbcXW9RsWnJUjNYfq6e2KMgDLDMvl4sr2baw/e67AZTGT6flgegrLuQy6t2xRk/9MbElTf7Rg8hTSmVBrR5NEmhd+sx978AG2nDjnyDcgae29RNfFU8RrG3Bl0gSj45guF9EFfC85j44tKGsEbE0n6y6fpTQbV7Z0U57bgaHODiamek8Ys4zA7MsnKXR/5AyDk/uKOtLe9igDUAWMbI764SGyHg/RcBhNSswZzbkPffxxvMkkbT292JqGK5dDSolpGAghSAUDTNaFaRoYJOP1cvbeezl/9+453nH14UuUzozSJAQnMws3AFKSqO3g3L3NjhqolIy2dtE00M22YwcROOm20bo6RltvvdgwUeuhdjSFlGUE6gQEIyMli/dKMTJfGemViBC88gdf4O7fv8mmU6dw5UykENi6zrW1XYy3tJDxeRlrbeH+V16jdnwCW9PQbJtT++7L1ygA+WC6Px5jvLmFRG1N+fddwQi5CPowlSLUtlne+/W/q/YwFsT2I+9zz5sHsTWBkTMRUjqpe02NvPvkxxltu36DhiYi1I6NEasLo5kW4dExYnW1zjGrNG95vgQmM9QPxkuunG0BvVsbip+4CULjKeqGi7tgaabJ9vffoG50gKHODt585ukFF8+50iZN/TGMnLOqnX5PW0DWaxCvhQ1nz+JOpfHH43RdvFQk/yFxpDxe+vKXGGtzDFLt6Bh3HzxIS28/Ga+XM3vucdIqV8nvVs3YOJ5UiommpgLJ60A0ysd+9FMCsRhSCDTLomfLZg4+/VTZYrXlzoG/+eT7Uso9sx9XBqCCdH54kf2/+nXZDJ+cy8Uvv/G1Valw2NLbx+YTJ3Fls3Rv2czVbVtvTvRMSqeAa8q3r+cs1lyOlKzsTQZdjHYsbEXXcWEMvZSrWUr0XJxrG5tJBxa3atqTyFI7lsKTNJG6IF7rYbLRXxDP0CyLR375K9ovXwEJumUhhWCoo533HvsI4y1OLCI8MsrT3/sBei6Xd4XkDIOr27fy9ieeKvg8a89fYPvRY7hTafo2rufM3j2kAyvfX+5JJum8eAlhS/o3ricZCoGUPPtf/p6a8YmC4kHTMDi9916O738YPZej68JFgtEo481NXFu/rqRsdnhkhM0nT+FNpujbsIHurZurJuRXzgAoF1AF2fXuoTnTO3XT5I7DR3j3yScqOKrqc88bv2fbsWPoORMNaOvuYcd7R3nxK1+6Ycm+ZtrUD8bxxx2XT86jM94SION3EQt7CUXSeSMgcQzEQt0/umlP6QaVXikHonH80UYaBiawdUF0RpP2hZAJuBkOlG/OAk4Tlzeee5bQ+AQNQ0OkgkGGOtqL3vueA78vmPzBEZxbf/Y8p/bty4uyTdciTHdyq5mYYNOp0/zqG19zJswVyuYTJ7nv1d85E7eU3Pfa7zi17376Nm4okg0BJ4C+7ehxrm7fxpM/+Cc028LImZiGQSoU5MUvf6lgp7f16DH2vPF7tKnezZ0XL7Hr0GF+85Xn52ywU2lUGmgFCURjcz6vSUnTteIG3rcztWNjbD96DNfU5A+OkF3t+Djbjh6f87VazmTNpQn88Vw+5dGdsWjujeJKm0Sa/Yy1Bcl4DXIujXith4F1tZjuBW7jbTlnf+N4uInQRArDtHFnLBoHYtQPxhf2njdJrL6Oq9u3MdTZUdLwtPT1l7z5pRA09/UBEBqfYPOpDwraeOq2jTuTXtHppLVjY9z32usYloUrl8NlmhiWxc7Dh2m72o0sY6jdmQwf/dk/40mncWdzaFLizuUIRibZ9/Kr+eO88QR7Xj+AMUOC3ZXLEZqYYOesnhnVRu0AlhA9l2PjB6fpvHiJjM9LvCaEL5EoG6SzcbR4bidqR8fYcvwE/nica+vWcvmOHQWr+s4PLyJKpO0ZpsnG02cKOorNRM9ZtF9yUjCLRPAk1I6lGG0PkazxkKxZXEkEy6U5mTmlnpTSES6b6RIQGqFImmiDf+HGZ5HIud24S2QESSHyUtlrurspJXOt286K9t0nl3qUS8Omkx+UrBcwciYtff0FEhIzidfU4EsUx31026bz4iU008Q2DDovXippRAzLYuPpMxxfrPali4AyAEuAPxaj7cpV7j74Nu5MGlfOZD6ZybZhlG6CvkLZeOoD9r3yWn4b3H7lKrvePcyv//ArCw6MNgw61a/lWg2604vTA6EUmj0l0FeUWyjRbLukn1ezbIKRBJHm5ZFNcu7u3ex+51BxsFgI+tevAxy/txQaUDwhWjOKz7zxBBvOnMEfTzDc0U7vpo03bCVZTbzJZMnmSAIwclku7djOhrPnCq6NaRicv3s3d75zqOQ5Bc53bBsgymVsQVnZ8GqxfL+llYiU7H31d3zmO9/lgZdewR+P533+2tSfaZmG6T+2EGRdLrJuN28/9QSjKyVNT0q88QTudLrk0650mn2vvFa0DfbH49zz+4P543o2byo5WZiGwcWdO4oen8abyM2Z7mi6lm6l7Y9lS/d/EaKs+8BRBo0u2ZhultP37eXaurWYhoFpGGTdLrIeN699/rN5A9a7eVPJCcs0DC7cuQuANVeu8rnv/GfufvMt7njvffb/6jc8+92/L9s5bjnQv2E9uRKxJdMw6Nu4gcvbtxXdo6f37uHcPXeXncAn6+ryvv3+jetLFnNaus7VbVsX8ZMsHLUDWEQ2nj7D5pMnyxZwTSNwMn4OPPM0yZoaDNNkrLVl2Wi0CMtCSFk2Y6G1u5sHf+sYOKRkpH0N7+/fjy+VIBUIMtrWypqr3dglqm1122bt+Qu885QT6I42NHBmzz1sf++o07YS59pM1tdz/u67Sr6/Nz53MZPEkXdeKjTTLr/Cs+2y184WS7cruVmkrvP6Z5+jbniY5v5rpH0++jZuKHDPZb1eDj79FA//5rdOdpNlYbpcjLW2cGbvvWimyaMv/LJgpWyYJjUTEzz9jz/gF3/89WW5E+jZspld7xyiZmIif69amuZcgw0beOYfv59vPQnOqv2OI+9xddtW3vvII+x5/UD+eRtHhuXY/oe5543f0/nhRbzJJFmPB5HJICxHbj1nGKQDfk4+sLyKzZQBWCC1Y2Nsf+8otWNjhEdHcZnz0yJx5XJ0XrrMhbt2037pMu2XL9O9dSsTzU1LOl7Nslh7/gJdFz4k53Zxcdcuhjs7AMd19cCLL9He3QNSYroMTu+5l5MPPZi/keuGR3jsp/9ccIO09Pbx9A/+KzmXC4EjkXD2nmKd9mnErOXzsUf207dhA5tPncKdzuT7y5YyiOHBODWRzJz9D2I1btKBpWv4Ua5zGDi5+eHxIaL1zY6Gj+1IF3dcOkNz/yXeffJx+jduWLKx3SwTzc1MNJdXCe3etpXh9nbWnzuHJ5VmYG0ng11dIATtly6XfI0AasfH2fXuIc7s2UNrTw9C2gx2dTkS1VLS2tNL/fAI8doa+jZuqOjix9Z1XvzK8+w8dIhNp88gbMnVrVs4+eA+th47UTImpVkW298/yjtPPUE8HGbnu4cJTk4y3tLMSFsrj/7yV/m4wvTvpqlpTDY2kA4E6N20kYu7dhYUfC4HlAFYAO2XLvORF36Z93HfjHfPFoLGawNsPHMWzTRBCO448j5n77mbox95ZEnGq+dyPPlff0R4bCzfm3Xd+Qucu/tuTjz0AJ/8h+8XBKldOZPd7xyipf8aL3/xCyAEu949VBQkmz7ePZUtEopE2PH+UTSr+EayNI3uEn2FRzraGelon3P87lSu7OQ/fe0zHo2JtuCc51ko5d08YHrdNA5+yLrzxxlpW8tQ12ZsodG/YTu9m+5gzeVuBjs7sJbZRDAXqVCQM3uLUsgxTBMhS0e3BLDz3cPsPHTEuV5TO4j+9WupHx7Fm0ig2za25jSOf/GrzxOtr1/iT3Id0+Pm+CP7Of5IoSJszfhYyR28JiU1445Y3LX167i2fh0Avnicz37nuyUDx4ZtUzMR4aUvf6moB/VyYfntz1YIwrZ5+DcvFvi4bybLW2oaNZGI83qmmlybJtuOHqOpv39Jxrz5xEnqRkfzaX0aziS//egx7jjyHp5UqmRbyebePlp7egFnB1AqgDYTTUp8iQRn9tyDaRjYUxNmzjBI+/0cfeTWZJjDw8k5nx9rCzC0LrzklaxZn4Es8RYSSPtdvPYHn8MfizDSvh7T5cJ2ubBcbqRuMNq2lrarw0s6vrLYkuBEiuaeSZp6o/hi2VsSHpxmsKuzpJGfxjBNXLkc7mwWdy7nZMtcukIgFsOYanaj2zaedJqnvv/DBY1lMRCWRePgcMmFnKnrJZslrTt3Yc5x27pO48DyTe1WO4BbpG54ZN7Ss7N/PWxNIxqupa6E/Kxummw6dZqR9jKrYSkJRSZxZdK0X7mKL55gqKuTnk0bb1imvvmD00VZH+BsbzecPlNWRVGTkvZLlxlc20W0vo6a8fEbrhykEIyuWcOLW7ey7dhx/PE4/evXcXHXzvl3qpKSwGSG8GgS3byBkRWQqK3MKisVcGG6dFxZq2A8UlyPPUQbWpxMGVF4pWzDQLMrL7UgbElL9ySu7HV1UW8yRzLkYawtcEtGM+PzcXrvHnYdOjzvxU+5rC1vKkVrdw+D6xaux6+ZJp2XLuOPxRhraWG4RCFcKTafPOV0kJv1uMS5Z69s24YnlSpoyenKZufsQSCkJLNMV/+gDMAtIzVtzmKg2RROFKLsJKgB4dFRHnjxJZKhIBd37SRRWwtAx8VLPPDSK7hTqfxkLYBNH5xmd00NL371+bkn1zLjFVISnIjM2VXMdDs+9VP77mfN1W7HbTUHmmUx1tpCMhTi7U/cWsJ4zViqZKP2kuO7QevGRUUIhjuDhEdSBKYygrJepwJ5uvPXUHvHHK+vfLA/GEkXTP7gCOP5YxlidR6yvluLmRx7dD+NAwO09vYV7AxtIW64U5xNx+XLCzYA4ZFRnvzhj9AsC92ysDWNSGMDL3/xCzf0v28+earkAgkcA/DJ7/0AkIw3NXPwk08RbWhgYG0XOw8dRssViw9KHCM5tox7NCsX0C0y0dRItsRka+Oke+VcBpaul5xUdcvCyOZKpqJJoH5omC2nPmDXoSM8992/p+v8BRoGBnn0F7/Cn0jkt8/XffU5aiYmuOvNt+Yc88WdOzBLZKcIQC8xzvxn0nWubHc6MY2uaePg00+R8XrJuVz5zzgT0zC4um3rgqQChC3nNflPjz89zzaOC0JKth95nz/4P/5PvvK3f8djP/8+nlQfPVvqGFwXLphEL9y1wykIK0Fmvu0hF5FANFPyWgo5lda6AF79wuf44P69ZN1uJwMrXMuFO3eSu0ndmwVLS0jJ4z/5GZ5UCnfW6QnsyuWoGx5hz+sHbvjyuVby3kwG3bLQLZuGwUGe/v4PcaXTjKxpY2BtZ8F9NZ0+mvF6efXzn13W4npqB3CrCMGBZ5/h4z/6KULaGKZFzjCwDIPffOV5wqOj3HvgTWoikeKX4hScxMK1hEdG81Z4+v6cDkJNB5Ye/s2LDHR1zbnq1m2bjWfOcvLBfTQODpGeXnnM+OW7cNduNpw5R+34uCMxPWM8s5l+zhaCo4/sJ9pwPUDXvW0rPVs2Uzs2hmW4CE1MsOeNA4THxsl4PZy99x5OLUBb3ZU2qRtOzHuHZQPp0NI3QN/91jvccfhIPgPKn0iw93dv4MrmOHNfYZA02liHLzGBN2EWVAXbAiLNiysSNx/KlyZRMp5xU+fWdY49sp9j+x921G01DSObpfPyFbR4HH0e36MtBN1btyxoHI0Dg7gz6eJ2j1MVuO8+8bE5J+Mr27dRM/7ODdO4NRw306YPTnN2z7288dyzbDl+kq3Hj+NJpZisq+fyzh1cvmPHskntLoeiTk+IAAAcXElEQVQyAAtgpL2dn/3pn7D55Elqx8cZbWvj0s47aO3p5ZFfv4humiVvOxunV23d8GjB42VTG4VG48DgDbdrRjbL5/+v72DrOkJKUoEAr37hs3l1Ucvl4sWvPs+6c+dZe/4CoYmJknEIgKzbzen79nB1+/a8MFjBmDSNSJOTshqrC/OLDetvMLr54UnkaO6LIuT8guo2YLp1kqGlzarRczl2Hj5S5CJwmSa733mHs/feXRSDGeoKUzOaoiaSRrMkWa/ORLMjVFdpEmEP7iGzWB1VQHKxjOeMQjjT7eZXf/hV9rx+gLXnz6NbhVLW0ztjiZMZdvLBfSRqFlYl7RQllv6t0c3r0uvlOHfP3Ww5cQp/LJZ3sZZzZblMk4bBIeezaBrn77mL8/eUrltZzigDsEDSwQCnHnwg/7OwbR787ctlfYngBAIHutbS1t07bx9cMhRyStjLPC9xfPm6bcP0DiIS4Ykf/pifffNf5PP4bV3n8h3O6qTrwoc8/OsXC8S+ACxNcGXH9oLPVSkahkpr+M/GqdB0Ar+RJt+Sb7PDo6NQxkUgbBt/PFHcNEQIok1+ok2VX/HPJl7rwR/N4Ek5RkAyFbSu95HzLs00kA4EOPjM0xx85mnqB4fY/fY71A8PE6utZay5mdqJCTI+HxfuurN80sNNMLqmDc0uvXofb2m+YVHajiPv4YvHEbY9dX0Eaa8XbypVdN+Zhk6ksXHBY642ygAsMrXj42WbuksgEQry9ieepHZsfN5ZRJplcfTRh3nsZy8UuIGmV1GWriNsu2ilogHuTJrWnl4GSgTXejdtJBkKEoxM5lc8Ekfn5YMyImxLiWbZGNkbqyZJIOvRGVxfGeE8VzrNo7/4ddksKWFLMr7lm+kBTAWua/AmcvhjWaQQJGo9ZCsROwHGW1t4/bPPLel7ZL1eTt1/HzsPH8lLsNg4C65Djz8252vDIyPsOnSkwP0jpHRcpbqeX1RNY2s6F3ftXPTPUGmUAVhkTMMoqxdiaxq//PrXyE4JoUlNK/rFgusT+8wy84F16zjw6Wd44KVXnNSzqbL8RChE38YNbH//fbQSVchC4kg2lEBqGr/5yvPsef0A68+dR7MsBrs6OfLYR/OZR5Vkru35TJeB1GB0TeW06He9e8hZGZZ4ztQ0urduXXYVniURgnTQTTq4AsZ6i5x86EEmGxrY9e5h/PE4o60tHH/4IcZvkImz/uy5kgsyl2ky1tSIL5ma6qcsSfsDHPj0M4ve8KcaVMUACCG+DXwKyAKXgD+SUhZHS1cg8XCYeG0NNWOFufK2EIy2teYn/4G1a0kGAwQnJ9FnSAuYus7VrVuoiUQcSYU99zDc4aQU9m3ayI83biAUiWC6XKSC1yteW3t7ab42UDQeISVjLeV/+bM+H28//RRvP/1U2WMqhdQEqYAL3yyht2l3RcatkQm4idX5sFyVS2DbcPZcycCgBKL19bzz5Mdu7cTTC4VlnCWyEunetpXumxRd002rbEGXbRj8+L/9JuGxMWyhEa2vu22+s2rtAF4B/kpKaQoh/gb4K+B/qNJYFp0Dz36Kp37wT2hTaWg5l4ucy8XBTz59/SAh+O3zX2L/r39DS18/tqZhGQaHHv8oV3dsL39yIUq2jDz66CN87Mc/nSVhqzPY2UGkaYX4KqXMZ6TMvBUlMLi2hpy38sFTh9I3u2UYnL/nrht2LZtNeGSU+177HS29fUhN4+rWrRx5/CMFBUaVxshaBCYzaLYkHXCRCrhum0luPvRu3sSWEyeL8vlNw+Dyju0gxG3h859NVQyAlPLlGT++C3y+GuNYKiKNjfzkm3/K+nPnqBkbJ9LcxNWtW4ominQwwCtf/AKeZBJXNkuipuaW1ROHOjv43WefY+/vXic8OobpcnHhzl0cffTWZBeqgTeZK1r9g2MADFNSXGpTGS7v2Mb2944W7wKkpHfjxps6V2Aiwh2HPuDqlvu5vO0BmgZ66PzwJJ8Y+AEv/PE3qtJ0PBBJUz+UyGdeBSNpsh6Doa4aKKHoejsy1NFO/4b1tF++kk+KMA2DaF2YD6ekr29HlkMM4I+Bfyr3pBDiz4A/A/DULK1S5mJietx8uPvOeR2b8fsX3CAFYGDdWn7xx99Ysa6FwGSmZO6/NvVcqkq+61P77qfzw0sEYjFHRE8IbF3n6P6HSYVuQnhOSlp7o/Sv347UnVtvYO1mRtu6uOvgr+m6eGnBufA3i2ba1A8liiqE3RmTmvEU0caV7+eeF0Jw4NPPsO7ceTafOIVumVzZto2Ld+686R3eSmLJDIAQ4lWgtcRTfy2lfGHqmL8GTOD75c4jpfwO8B2AUNvm5dVOZ7mywib+aebM/a+iUFjO4+GX3/gaG86eo/3SZdJ+Hx/eeecNA4uz8cVz2LonP/kDSE0n53Iz3L6Rxv5rFTcA5aqANQnByczqMQAAQnB1+zaubt9W7ZFUjCUzAFLKOSNjQoivA88Aj0u5zPqkKapCosaDL54tqgOwBYve1/dmsQ2Di7t2Lij1z5vIYuvFt5zUDUZbO7FciYUM8ZaYq0XhcmtfqFh8qqIFJIR4Cifo+2kp5dwav4pVQyroIu13MVMs0xaQ8bmWvNK3Eti6RrmuEa5chit3lG+BuVSkgu6SIoES0CxJY38M1xL2V1ZUl2rFAP4j4AFeEY674l0p5beqNBbFckEIRjpC+GNZApNOT9lErceZ/Cvo1vLFstSOpdBzFlmvwWSjf1EKphK1HmrGU0VxDs00GepsqkoWkGVoZSWap4XifLEsIx1B0sHq7sIUi0+1soA2VeN9FSsAIUjWeKrm8gmNpQiPJvNuKD2Rw5ucZLijhswC20yabkcyun7IcfVMu1gmmgJEWpa2i1k53GkTqYEoU4A9rTrbeC1O3+bKGmLF0qPkoBWKKYQtCyZ/cCY/TZKftBdKIuxlqCNE1qNjGhqJkId4uHr5/7YmyvaJmIlmO7UCituL5ZAGqlBUHXcqR/1geQlqV9ZC2BK5wLx4XzxLY38sn/FkxLL441mGO0LYhoYUAtNduVqAnEd33EA5+4bqq660iVmFXgaKpUN9m4pVjzeRo6kvOrcKqVi4bj5S0jAQL9phCAktvbH8+U2Xzkh7sDKTrRAMd4Ro7YkiLFnQaGg2t1qkqFi+qG9Useqpm1UINRsbSCxCIHp6F1GKaVeTJp3jWrujZY9dbEyPQd/GOsZaA3Mel/Ut7+YmiptH7QAUVcUbz1I3ksSVsbAMjWi9l1idt3LBRlviKuPbnhahM906Ey1zT47zYS6105k4uwKJP5ohEa6QzLQmSIa9JBJZArFiMb5UwIVtKANwu6EMgKJq+GJZGq/F8qtvw7QJjyTRc1blsmLmmJMlMN4cIBH2LIpBMl0alktDZG/sb5/eCVSa8bYQmh3Dm8jl9bczfoPR9srJbysqhzIAiqpRN1zsetEkhCIZog1+bKMCHkoJli7QLVm06rVc2qJN/oBT57AmREtPFCFlvjMXFNshW0C2CgFXqQlGOmvQsxaunIXp0isalFZUFmUAFNVBSoxc6eRzKQTujEnaWPrq35qJFJpdumX6aFtw0V1ROa9B/8YwgckMrqyFrWtFxWHT7S6rWf1suXUsNfHf9igDoFhS9JxNeDiBP+6IjiWDbiItASxdIAUl0y6FlFiVWP0DwUimZABYCnBnLbJL0MBd6hrx+uu5/xm/i/rBOPqMVExNQtvVSUY6QmoFrlgyVBaQYskQlk3r1QiBWDaf4RKIZWm9GkHYknjYU6D7A87q13Tr5Crk/phTDK1CWTjpgItIow/E9crb6RhAS0+0qkqoitsbtQNQLBnBqQ5TM+d4gSMyFpzMMNEUwMjZTsBxCsvQGO6oXMAxGXQTimRKuoBSgcq5YGrH0kU7EedaOdenkn18hS0JRtKOHpOAeI2HeNi7aprDrCaUAVAsGd5ErqR7RZNO969YvY+RjhqMjIU7Y2IZGhmfUVG9mclGP/5YFs2W+bHaAuK1HkxP5VwvhllGjAfKxkqWBFvS0j2JK2vlr4crnSQUSZP1GgjLJh1wk6xxq7TQ2wBlABRLhunSkBRnuEjAnOHjNz16RSfbmdiGxsCGMKHxNP54FksXxOq8Fe8+lvXoeFOlZZezXh2kRDclti4WLEcxF4FopmDyB8dP7MrauLJZBOBPmNQPJ0kFXIytCWLrypO8UlEGQLFkxOu8BEu0eZTCeW65YOsak01+Jpuq1/0q0uSnubdQjsIWjlaPK23S3BdDTLnTEiE3463BJTEE/lhxQx6gyI0H4EvkaO6JMriuVqmErlCUAVAsGTmPwXhrgPrBxPVZQ8JYa6BiQd65aOnp5c533qVmYoKJxkZOPvgAo2vaqjKWjN/FSHuI+qGE4/KZSgNN+wzqhwsVSv2xLLoZY7irZtHHITVK7tpKIQB3xsKTNBcsla2oDtW/CxW3NTm3Tirgxp0xybl1Jpr9FVeUDExO4k2miDQ25Bt8rz9zlgd/+zKG6bhd/NEYbT29vPHsp+jfuKGi45smHXRzLehGWBKpAUKw5tJEyWI5TyqHkbEW3XWWDHnwx3I3PnAGDQMxrm2oU0HiFYgyAIolo24gTmiqs5fACWZ6uycZ7Kol59GvLzWXyH3gj8X4yD//grqRUWxNQ0jJiQf3cWbPvdz/6mv5yR8cP7dmmux7+VV++q0/rapLQ+rX37tsAFiAK2suugEwjZv73ALQTUkgliVRqzqGrTSUAVAsCcHxJKHJTLHv2Iam/piTdWNJbE0QrfcSbfAt7qQrJU/88EeEIpNoM/Lod7/1DkgnvbIU3lQSfzxOMrQ8tG8sQyudISQd2ehFfz+XXrZAr5xrSAP8sYwyACsQFb5XLD5SUjeSKttr1sjZee0d3ZbUjqUIDycX9f1bevrwxhNITSPlD2JpzmTpMk02nzhZtgBM2JKca/n4sycbvCWL5XIenZx38ddvlksn43Mx2+TYU+9b6qpJpjqLKVYcagegWHSMrD1nm8HZU4UjAJdmstGHXEhKoZTUjKWoGU+jWz7e/fgXQRMI25nO2q+cZcPZY/iTSSbr66kbGSnYHdhCMNTZQc67fDKU4mEvuuV8rrw6p29p1TlH2oM09cfwpMz8eyZDbixdUDORKTpeTo1TsfJQBkCx6Ni6mFcWSQECXDmb7AIMQHgkSWhiqqJWCKTh/HrLqdV///rtIKF2op/ff/oZnvrBDzFyOYxcDtMwyPh8HHz6E7f8/kuCEEw2+onW+zCmxOMs19Ju3KWuMdxVi5G10HM2pkfH1gQdH46X/F6lLsgsgWaSYulRBkCx6NiGRtrvwpvMzdsQCFlYHFaAlPhjWWdlb9qk/QaTjf4CkTRhyeuTf9lxuejfsJ3LvnXE6sL89Jv/gs6Ll6iZiBBprKdv48Zl2/ZQaqLA5WNksjRfu4bpMhhZs2ZJxm26r0tBe5I5J0ZTwnWmWXJR+iUrKo8yAIolYXRNkJbeKEbGmrPPLDj+5axHJzySRLMlyZDbkUKeCgoXrOyBQDSLP5ZlcG1tflI0clbeXTEXtmEw1NWV/3f3tq0L+pzVYNv7R7n3wJvYmgZILMPF6595lpH2NYUHyhkT8zwC7MKynRoDS5LxGQWyHLZWevLPv5Wa+1ckygAolgTb0BhYV4s7laO1J1bymOmgomUIp6Ao7RgLXzxLaFxnqKsWzZbUTKQLslLE1IvrhpP5YijL0G44+YPj51/J0gWt3d3cc+DNghRWsjk+9uOf8pNv/Wk+fuGfTFM3nES3JFJAotbDeHOgdK6+lITG09SNXA/ES+H0ZRC2BM2pPrZ1DW1WRpIEUkGXqgReoazcO0Gx/BGCrG9u3/BkgxPk1OT1XYImnQrTUCSNN5kruboUgDd1vWDJNjTSgeLslZnYQCzsXdGuip2HjuAyizWDhG2z/ux5APzRDA2DCYypTCtNQmAyQ9M1xxALyyYYSVM7ksQXzdDUG6VuJJnfqeUb1NvSqY+wITCZzWf7TGcl2cLRexprrVD7TsWio3YAiqVFCBIhV8lG49MTSamcc00yJRldXp/HnrXqHG0L0nFxouROQOKIqkWaq6f3sxgEoqV3Uy7TxB93nguPJEtWD3sTOXzRDI2DcZDOdc/X4pU458zHNADLZqwlgAboOYus13BE89Tqf8WidgCKJWe8NUjOo+dzyW3A1mBoXS03yhdKB1yUathoC0jUuPFPZvDFMo6vW9cw58iQSd8Gk9VI+5oiwweQc7kYa20BylcPCwmN1+JoNvkdl8b8dH9gSoIiYxEPe5lsCpAKLWK/ZEVVUDsAxZIjdSce4E3mcKctTJdGMugGTZCsoagnLkxp8tc4E/ZIR4jmvuj1VatwUk1DkQyhyPW89IkmH8mQB2M8VbQCloKKSzwvBaf23ce6c+fRcjOa6GgayVCQvo0bAefa6FbxNmihU7UtwNQhEEnjj2WRmiAe9pD2qxjASkXtABSVQQjSATfxWk++6TtSkvMYzmNc99zYwhGRi9c5fXMzfhd9G+sZbwkQafITafChmbLAZy2AupEUluEEeWdWz043WM8uQeVspYnV1fHbL3+RofZ2J4Cu61zdtpUXv/K8kwoqpROwLfP6BU3TEoKxHPVDCfyJHP5Ylqa+GHVDiYWcVVFFVv4doVgZSEndUILQZMYJ6konc2esNUAgmkHirEYkzl+JkDsfrNVzlqNTP9WNqnYkUXLlIoDwSIprG2oJRjIEYllsTRALe0nWrPzV/zTjLS389itfup6WObX6dqdyTt8AKQsyYucz6c8lAT19nqxHwz2jWYzA2ZEFJzPEw94lkaZQLC3qG1NUhOBEOt8cZtrdI3L21IR1ffKZXs2Hx1Ikwl68iSwNg84KU0ioGU/Pme6p2RKEINroJ9q4sgO+N2SG20VYNi29UbRZS/8bZcZO77zmmvynjYknY5cOFkunR8GkMgArDvWNKSpC7XjppufI8pOPP5albjhR8LrpzJW5Jq1SQdLbHX8sW3K2X+iVELP+r7i9UDEARUUoJ788F+506R65M5qLFSBxfP2rsTGJbtol02mhMOV29iEzU0DnUUdX+vyC28rFtppQBkBREbJzdAErZRrEVPFSuUnN0qaqVbn+J+vRGWsNLMJoVx5Zn1GyYE4CyaCLaJ0XU5TP95/+I2e87kZMG5ZYnXdZtPhU3DxV/daEEH8JfBtoklKOVnMsiqUl0ly66Xna58IwLYycjSYLA5flpH0kkKz1MtHsx5vIYeRsch69QLtmtZH2u5wG8pnrQVqJYyQjjX4ahhLo85jVBVNZU0G3E3gvc5zESdON13lvWO2tWL5UzQAIITqBjwM91RqDonJk/C6GO2qoG07gzlhITRALe4g0+kE4PuzakSSuXGGgcdoITD9m48gPT051EEvfBrn9i4IQDHXVEh5OEIxmEDak/QYTzQHcWQt32rwpZVbDmiQYTZMMhEAvnCZsAZFGH7GG2zzIvgqo5g7gb4F/A7xQxTEoKkgm4GJwfdhJX5y1Uk/WeAhP6dGUwjQEtiZIBd1E633Y5aSjVzFSE0y0BpmYpc1TO1ZcGDcXObfGYz/7ObppMdy+nv7120kFQti6AdJivD2s2j/eJlTFAAghPg30SylPiBts2YUQfwb8GYCnpqkCo1MsOWW+c1vXoISMgRQw2ehXXaduESlEyaypUnUCtgBXdgIA3bZo671IW+/F/POJUJCf/DffXMrhKirIkhkAIcSrQGuJp/4a+LfAE/M5j5TyO8B3AEJtm281UUGxAojWe2kYiJdcrSZCytVzq8TDHvyx4oC6I4/hwpcwnV7Ibp2JFj8dl66V7ZnsymYrMGJFpVgyAyCl/Fipx4UQu4D1wPTqvwM4KoS4T0o5uFTjUSx/kiE37rSXmom0szoVzl/DHaGF9Qpe5WR8BvGwh2DkuhHI9whoCVzv9DW1Mxvq7Mz3UZ6JDQx0dlZw5IqlpuIuICnlKaB5+mchxFVgj8oCUiAEkeYA0Xqf0wdAE6T8rlWZ17+oCMFES5BErRd/1BHPS4bchdk7M9xysbowl3dsZ/3Zc/neA7YQmC4XRx/dX9GhK5YWlbyrWHbYhkayRgUZF5us15i3IN47Tz3ByJo2drx3FE86zWBXJyceeoBoff0Sj1JRSapuAKSU66o9BoVCMQshuLj7Ti7uvrPaI1EsIcqxqlAoFKsUZQAUCoVilaIMgEKhUKxSlAFQKBSKVYoyAAqFQrFKUQZAoVAoVinKACgUCsUqRRkAhUKhWKUoA6BQKBSrFGUAFAqFYpWiDIBCoVCsUpQBUCgUilWKMgAKhUKxSlEGQKFQKFYpygAoFArFKkUZAIVCoVilKAOgUCgUqxQhpaz2GOaNEGIE6K72OMrQCKz2vsbqGjio66CuASyva7BWStk0+8EVZQCWM0KI96SUe6o9jmqiroGDug7qGsDKuAbKBaRQKBSrFGUAFAqFYpWiDMDi8Z1qD2AZoK6Bg7oO6hrACrgGKgagUCgUqxS1A1AoFIpVijIACoVCsUpRBmAJEEL8pRBCCiEaqz2WSiOE+LYQ4pwQ4qQQ4udCiHC1x1QphBBPCSHOCyEuCiH+x2qPp9IIITqFEK8LIc4KIU4LIf51tcdULYQQuhDimBDiV9Uey1woA7DICCE6gY8DPdUeS5V4BdgppbwTuAD8VZXHUxGEEDrwn4BPADuA54UQO6o7qopjAv+9lHI7sA/481V4Dab518DZag/iRigDsPj8LfBvgFUZXZdSviylNKd+fBfoqOZ4Ksh9wEUp5WUpZRb4IfBslcdUUaSUA1LKo1P/juFMgO3VHVXlEUJ0AJ8E/nO1x3IjlAFYRIQQnwb6pZQnqj2WZcIfAy9WexAVoh3onfFzH6tw8ptGCLEOuBs4VN2RVIX/gLMItKs9kBthVHsAKw0hxKtAa4mn/hr4t8ATlR1R5ZnrGkgpX5g65q9xXALfr+TYqogo8diq3AUKIYLAT4G/kFJGqz2eSiKEeAYYllK+L4T4SLXHcyOUAbhJpJQfK/W4EGIXsB44IYQAx/VxVAhxn5RysIJDXHLKXYNphBBfB54BHperp9CkD+ic8XMHcK1KY6kaQggXzuT/fSnlz6o9nirwEPBpIcTTgBeoEUJ8T0r51SqPqySqEGyJEEJcBfZIKZeLGmBFEEI8Bfx74FEp5Ui1x1MphBAGTtD7caAfOAJ8WUp5uqoDqyDCWfn8f8C4lPIvqj2eajO1A/hLKeUz1R5LOVQMQLHY/EcgBLwihDguhPi/qz2gSjAV+P6XwEs4wc8frabJf4qHgK8Bj01998enVsKKZYraASgUCsUqRe0AFAqFYpWiDIBCoVCsUpQBUCgUilWKMgAKhUKxSlEGQKFQKFYpygAoFIuEEOK3QojIcleAVCimUQZAoVg8vo2TB69QrAiUAVAobhIhxN6pfgdeIURgSvt+p5TyNSBW7fEpFPNFaQEpFDeJlPKIEOIXwP8K+IDvSSk/qPKwFIqbRhkAheLW+F9w9H7SwL+q8lgUiltCuYAUilujHgji6B55qzwWheKWUAZAobg1vgP8Tzj9Dv6mymNRKG4J5QJSKG4SIcQfAqaU8gdTvYDfFkI8BvzPwDYgKIToA/5ESvlSNceqUMyFUgNVKBSKVYpyASkUCsUqRRkAhUKhWKUoA6BQKBSrFGUAFAqFYpWiDIBCoVCsUpQBUCgUilWKMgAKhUKxSvn/AbTD+WXFivuFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_decision_boundary(lambda x: clf.predict(x), X, Y) #绘制决策边界\n",
    "plt.title(\"Logistic Regression\") #图标题\n",
    "\n",
    "\"\"\"\n",
    "    在具有两个类的统计分类问题中，决策边界或决策表面是超曲面，\n",
    "    其将基础向量空间划分为两个集合，一个集合。 分类器将决策边\n",
    "    界一侧的所有点分类为属于一个类，而将另一侧的所有点分类为\n",
    "    属于另一个类。\"\"\"\n",
    "LR_predictions  = clf.predict(X.T) #预测结果\n",
    "print (\"逻辑回归的准确性： %d \" % float((np.dot(Y, LR_predictions) + \n",
    "        np.dot(1 - Y,1 - LR_predictions)) / float(Y.size) * 100) +\n",
    "       \"% \" + \"(正确标记的数据点所占的百分比)\")\n",
    "\"\"\"\n",
    "    逻辑回归绘制决策边界\n",
    "    Y是一个只含1与0的向量，通过计算来得到红色的点在红色部分，\n",
    "    蓝色的点在蓝色部分的数量，再除以总的点数，\n",
    "    就得到了准确性\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 定义神经网络结构\n",
    "在构建之前，我们要先把神经网络的结构给定义好：\n",
    "\n",
    "* n_x: 输入层的数量\n",
    "* n_h: 隐藏层的数量（这里设置为4）\n",
    "* n_y: 输出层的数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def layer_sizes(X , Y):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "     X - 输入数据集,维度为（输入的数量，训练/测试的数量）\n",
    "     Y - 标签，维度为（输出的数量，训练/测试数量）\n",
    "    \n",
    "    返回：\n",
    "     n_x - 输入层的数量\n",
    "     n_h - 隐藏层的数量\n",
    "     n_y - 输出层的数量\n",
    "    \"\"\"\n",
    "    n_x = X.shape[0] #输入层\n",
    "    n_h = 4 #，隐藏层，硬编码为4\n",
    "    n_y = Y.shape[0] #输出层\n",
    "    \n",
    "    return (n_x,n_h,n_y)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试layer_sizes=========================\n",
      "输入层的节点数量为: n_x = 5\n",
      "隐藏层的节点数量为: n_h = 4\n",
      "输出层的节点数量为: n_y = 2\n"
     ]
    }
   ],
   "source": [
    "#测试layer_sizes\n",
    "print(\"=========================测试layer_sizes=========================\")\n",
    "X_asses , Y_asses = layer_sizes_test_case()\n",
    "(n_x,n_h,n_y) =  layer_sizes(X_asses,Y_asses)\n",
    "print(\"输入层的节点数量为: n_x = \" + str(n_x))\n",
    "print(\"隐藏层的节点数量为: n_h = \" + str(n_h))\n",
    "print(\"输出层的节点数量为: n_y = \" + str(n_y))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 初始化模型的参数\n",
    "在这里，我们要实现函数initialize_parameters()。我们要确保我们的参数大小合适，如果需要的话，请参考上面的神经网络图。\n",
    "我们将会用随机值初始化权重矩阵。\n",
    "\n",
    "* np.random.randn(a，b)* 0.01来随机初始化一个维度为(a，b)的矩阵。\n",
    "将偏向量初始化为零。\n",
    "\n",
    "* np.zeros((a，b))用零初始化矩阵（a，b）。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def initialize_parameters( n_x , n_h ,n_y):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "        n_x - 输入层节点的数量\n",
    "        n_h - 隐藏层节点的数量\n",
    "        n_y - 输出层节点的数量\n",
    "    \n",
    "    返回：\n",
    "        parameters - 包含参数的字典：\n",
    "            W1 - 权重矩阵,维度为（n_h，n_x）\n",
    "            b1 - 偏向量，维度为（n_h，1）\n",
    "            W2 - 权重矩阵，维度为（n_y，n_h）\n",
    "            b2 - 偏向量，维度为（n_y，1）\n",
    "\n",
    "    \"\"\"\n",
    "    np.random.seed(2) #指定一个随机种子，以便你的输出与我们的一样。\n",
    "    W1 = np.random.randn(n_h,n_x) * 0.01\n",
    "    b1 = np.zeros(shape=(n_h, 1))\n",
    "    W2 = np.random.randn(n_y,n_h) * 0.01\n",
    "    b2 = np.zeros(shape=(n_y, 1))\n",
    "    \n",
    "    #使用断言确保我的数据格式是正确的\n",
    "    assert(W1.shape == ( n_h , n_x ))\n",
    "    assert(b1.shape == ( n_h , 1 ))\n",
    "    assert(W2.shape == ( n_y , n_h ))\n",
    "    assert(b2.shape == ( n_y , 1 ))\n",
    "    \n",
    "    parameters = {\"W1\" : W1,\n",
    "              \"b1\" : b1,\n",
    "              \"W2\" : W2,\n",
    "              \"b2\" : b2 }\n",
    "    \n",
    "    return parameters\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试initialize_parameters=========================\n",
      "W1 = [[-0.00416758 -0.00056267]\n",
      " [-0.02136196  0.01640271]\n",
      " [-0.01793436 -0.00841747]\n",
      " [ 0.00502881 -0.01245288]]\n",
      "b1 = [[0.]\n",
      " [0.]\n",
      " [0.]\n",
      " [0.]]\n",
      "W2 = [[-0.01057952 -0.00909008  0.00551454  0.02292208]]\n",
      "b2 = [[0.]]\n"
     ]
    }
   ],
   "source": [
    "#测试initialize_parameters\n",
    "print(\"=========================测试initialize_parameters=========================\")    \n",
    "n_x , n_h , n_y = initialize_parameters_test_case()\n",
    "parameters = initialize_parameters(n_x , n_h , n_y)\n",
    "print(\"W1 = \" + str(parameters[\"W1\"]))\n",
    "print(\"b1 = \" + str(parameters[\"b1\"]))\n",
    "print(\"W2 = \" + str(parameters[\"W2\"]))\n",
    "print(\"b2 = \" + str(parameters[\"b2\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 循环\n",
    "### 前向传播\n",
    "我们现在要实现前向传播函数forward_propagation()。\n",
    "我们可以使用sigmoid()函数，也可以使用np.tanh()函数。\n",
    "步骤如下：\n",
    "\n",
    "* 使用字典类型的parameters（它是initialize_parameters() 的输出）检索每个参数。\n",
    "* 实现向前传播, 计算$ Z^{[1]}, A^{[1]}, Z^{[2]}$ 和 $A^{[2]}$ \n",
    " （ 训练集里面所有例子的预测向量）。\n",
    "* 反向传播所需的值存储在“cache”中，cache将作为反向传播函数的输入。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def forward_propagation( X , parameters ):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "         X - 维度为（n_x，m）的输入数据。\n",
    "         parameters - 初始化函数（initialize_parameters）的输出\n",
    "    \n",
    "    返回：\n",
    "         A2 - 使用sigmoid()函数计算的第二次激活后的数值\n",
    "         cache - 包含“Z1”，“A1”，“Z2”和“A2”的字典类型变量\n",
    "     \"\"\"\n",
    "    W1 = parameters[\"W1\"]\n",
    "    b1 = parameters[\"b1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "    b2 = parameters[\"b2\"]\n",
    "    #前向传播计算A2\n",
    "    Z1 = np.dot(W1 , X) + b1\n",
    "    A1 = np.tanh(Z1)\n",
    "    Z2 = np.dot(W2 , A1) + b2\n",
    "    A2 = sigmoid(Z2)\n",
    "    #使用断言确保我的数据格式是正确的\n",
    "    assert(A2.shape == (1,X.shape[1]))\n",
    "    cache = {\"Z1\": Z1,\n",
    "             \"A1\": A1,\n",
    "             \"Z2\": Z2,\n",
    "             \"A2\": A2}\n",
    "    \n",
    "    return (A2, cache)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试forward_propagation=========================\n",
      "-0.0004997557777419902 -0.000496963353231779 0.00043818745095914653 0.500109546852431\n"
     ]
    }
   ],
   "source": [
    "#测试forward_propagation\n",
    "print(\"=========================测试forward_propagation=========================\") \n",
    "X_assess, parameters = forward_propagation_test_case()\n",
    "A2, cache = forward_propagation(X_assess, parameters)\n",
    "print(np.mean(cache[\"Z1\"]), np.mean(cache[\"A1\"]), np.mean(cache[\"Z2\"]), np.mean(cache[\"A2\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 计算损失\n",
    "计算成本的公式如下：\n",
    "$$\n",
    "J = - \\frac{1}{m} \\sum\\limits_{i = 0}^{m} \\large\\left(\\small y^{(i)}\\log\\left(a^{[2] (i)}\\right) + (1-y^{(i)})\\log\\left(1- a^{[2] (i)}\\right) \\large \\right) \\small \\tag{6}\n",
    " $$\n",
    "\n",
    "有很多的方法都可以计算交叉熵损失，比如下面的这个公式，我们在python中可以这么实现：\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_cost(A2,Y,parameters):\n",
    "    \"\"\"\n",
    "    计算方程（6）中给出的交叉熵成本，\n",
    "    \n",
    "    参数：\n",
    "         A2 - 使用sigmoid()函数计算的第二次激活后的数值\n",
    "         Y - \"True\"标签向量,维度为（1，数量）\n",
    "         parameters - 一个包含W1，B1，W2和B2的字典类型的变量\n",
    "    \n",
    "    返回：\n",
    "         成本 - 交叉熵成本给出方程（13）\n",
    "    \"\"\"\n",
    "    \n",
    "    m = Y.shape[1]\n",
    "    W1 = parameters[\"W1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "    \n",
    "    #计算成本\n",
    "    logprobs = logprobs = np.multiply(np.log(A2), Y) + np.multiply((1 - Y), np.log(1 - A2))\n",
    "    cost = - np.sum(logprobs) / m\n",
    "    cost = float(np.squeeze(cost))\n",
    "    \n",
    "    assert(isinstance(cost,float))\n",
    "    \n",
    "    return cost\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试成本函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试compute_cost=========================\n",
      "cost = 0.6929198937761266\n"
     ]
    }
   ],
   "source": [
    "#测试compute_cost\n",
    "print(\"=========================测试compute_cost=========================\") \n",
    "A2 , Y_assess , parameters = compute_cost_test_case()\n",
    "print(\"cost = \" + str(compute_cost(A2,Y_assess,parameters)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 后向传播\n",
    "为了计算dZ1，里需要计算 $g^{[1]'}(Z^{[1]})$, $g^{[1]}(...)$是tanh激活函数，如果$a = g^{[1]}(z)a=g[1](z)$ 那么$g^{[1]'}(z) = 1-a^2 $ 。所以我们需要使用 (1 - np.power(A1, 2))来计算$g^{[1]'}(Z^{[1]})$\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def backward_propagation(parameters,cache,X,Y):\n",
    "    \"\"\"\n",
    "    使用上述说明搭建反向传播函数。\n",
    "    \n",
    "    参数：\n",
    "     parameters - 包含我们的参数的一个字典类型的变量。\n",
    "     cache - 包含“Z1”，“A1”，“Z2”和“A2”的字典类型的变量。\n",
    "     X - 输入数据，维度为（2，数量）\n",
    "     Y - “True”标签，维度为（1，数量）\n",
    "    \n",
    "    返回：\n",
    "     grads - 包含W和b的导数一个字典类型的变量。\n",
    "    \"\"\"\n",
    "    m = X.shape[1]\n",
    "    \n",
    "    W1 = parameters[\"W1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "    \n",
    "    A1 = cache[\"A1\"]\n",
    "    A2 = cache[\"A2\"]\n",
    "    \n",
    "    dZ2= A2 - Y\n",
    "    dW2 = (1 / m) * np.dot(dZ2, A1.T)\n",
    "    db2 = (1 / m) * np.sum(dZ2, axis=1, keepdims=True)\n",
    "    dZ1 = np.multiply(np.dot(W2.T, dZ2), 1 - np.power(A1, 2))\n",
    "    dW1 = (1 / m) * np.dot(dZ1, X.T)\n",
    "    db1 = (1 / m) * np.sum(dZ1, axis=1, keepdims=True)\n",
    "    grads = {\"dW1\": dW1,\n",
    "             \"db1\": db1,\n",
    "             \"dW2\": dW2,\n",
    "             \"db2\": db2 }\n",
    "    \n",
    "    return grads\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试backward_propagation=========================\n",
      "dW1 = [[ 0.01018708 -0.00708701]\n",
      " [ 0.00873447 -0.0060768 ]\n",
      " [-0.00530847  0.00369379]\n",
      " [-0.02206365  0.01535126]]\n",
      "db1 = [[-0.00069728]\n",
      " [-0.00060606]\n",
      " [ 0.000364  ]\n",
      " [ 0.00151207]]\n",
      "dW2 = [[ 0.00363613  0.03153604  0.01162914 -0.01318316]]\n",
      "db2 = [[0.06589489]]\n"
     ]
    }
   ],
   "source": [
    "#测试backward_propagation\n",
    "print(\"=========================测试backward_propagation=========================\")\n",
    "parameters, cache, X_assess, Y_assess = backward_propagation_test_case()\n",
    "\n",
    "grads = backward_propagation(parameters, cache, X_assess, Y_assess)\n",
    "print (\"dW1 = \"+ str(grads[\"dW1\"]))\n",
    "print (\"db1 = \"+ str(grads[\"db1\"]))\n",
    "print (\"dW2 = \"+ str(grads[\"dW2\"]))\n",
    "print (\"db2 = \"+ str(grads[\"db2\"]))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 更新参数\n",
    "我们需要使用(dW1, db1, dW2, db2)来更新(W1, b1, W2, b2)。\n",
    "更新算法如下：\n",
    "$$ \\theta = \\theta - \\alpha \\frac{\\partial J }{ \\partial \\theta } $$\n",
    "\n",
    "* $α$：学习速率\n",
    "* $θ$ ：参数\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_parameters(parameters,grads,learning_rate=1.2):\n",
    "    \"\"\"\n",
    "    使用上面给出的梯度下降更新规则更新参数\n",
    "    \n",
    "    参数：\n",
    "     parameters - 包含参数的字典类型的变量。\n",
    "     grads - 包含导数值的字典类型的变量。\n",
    "     learning_rate - 学习速率\n",
    "    \n",
    "    返回：\n",
    "     parameters - 包含更新参数的字典类型的变量。\n",
    "    \"\"\"\n",
    "    W1,W2 = parameters[\"W1\"],parameters[\"W2\"]\n",
    "    b1,b2 = parameters[\"b1\"],parameters[\"b2\"]\n",
    "    \n",
    "    dW1,dW2 = grads[\"dW1\"],grads[\"dW2\"]\n",
    "    db1,db2 = grads[\"db1\"],grads[\"db2\"]\n",
    "    \n",
    "    W1 = W1 - learning_rate * dW1\n",
    "    b1 = b1 - learning_rate * db1\n",
    "    W2 = W2 - learning_rate * dW2\n",
    "    b2 = b2 - learning_rate * db2\n",
    "    \n",
    "    parameters = {\"W1\": W1,\n",
    "                  \"b1\": b1,\n",
    "                  \"W2\": W2,\n",
    "                  \"b2\": b2}\n",
    "    \n",
    "    return parameters\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试update_parameters=========================\n",
      "W1 = [[-0.00643025  0.01936718]\n",
      " [-0.02410458  0.03978052]\n",
      " [-0.01653973 -0.02096177]\n",
      " [ 0.01046864 -0.05990141]]\n",
      "b1 = [[-1.02420756e-06]\n",
      " [ 1.27373948e-05]\n",
      " [ 8.32996807e-07]\n",
      " [-3.20136836e-06]]\n",
      "W2 = [[-0.01041081 -0.04463285  0.01758031  0.04747113]]\n",
      "b2 = [[0.00010457]]\n"
     ]
    }
   ],
   "source": [
    "#测试update_parameters\n",
    "print(\"=========================测试update_parameters=========================\")\n",
    "parameters, grads = update_parameters_test_case()\n",
    "parameters = update_parameters(parameters, grads)\n",
    "\n",
    "print(\"W1 = \" + str(parameters[\"W1\"]))\n",
    "print(\"b1 = \" + str(parameters[\"b1\"]))\n",
    "print(\"W2 = \" + str(parameters[\"W2\"]))\n",
    "print(\"b2 = \" + str(parameters[\"b2\"]))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 整合\n",
    "我们现在把上面的东西整合到nn_model()中，神经网络模型必须以正确的顺序使用先前的功能。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def nn_model(X,Y,n_h,num_iterations,print_cost=False):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "        X - 数据集,维度为（2，示例数）\n",
    "        Y - 标签，维度为（1，示例数）\n",
    "        n_h - 隐藏层的数量\n",
    "        num_iterations - 梯度下降循环中的迭代次数\n",
    "        print_cost - 如果为True，则每1000次迭代打印一次成本数值\n",
    "    \n",
    "    返回：\n",
    "        parameters - 模型学习的参数，它们可以用来进行预测。\n",
    "     \"\"\"\n",
    "     \n",
    "    np.random.seed(3) #指定随机种子\n",
    "    n_x = layer_sizes(X, Y)[0]\n",
    "    n_y = layer_sizes(X, Y)[2]\n",
    "    \n",
    "    parameters = initialize_parameters(n_x,n_h,n_y)\n",
    "    W1 = parameters[\"W1\"]\n",
    "    b1 = parameters[\"b1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "    b2 = parameters[\"b2\"]\n",
    "    \n",
    "    for i in range(num_iterations):\n",
    "        A2 , cache = forward_propagation(X,parameters)\n",
    "        cost = compute_cost(A2,Y,parameters)\n",
    "        grads = backward_propagation(parameters,cache,X,Y)\n",
    "        parameters = update_parameters(parameters,grads,learning_rate = 0.5)\n",
    "        \n",
    "        if print_cost:\n",
    "            if i%1000 == 0:\n",
    "                print(\"第 \",i,\" 次循环，成本为：\"+str(cost))\n",
    "    return parameters\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试nn_model=========================\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\SpacialSoftware\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:19: RuntimeWarning: divide by zero encountered in log\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "W1 = [[-3.89167767  4.77541602]\n",
      " [-6.77960338  1.20272585]\n",
      " [-3.88338966  4.78028666]\n",
      " [ 6.77958203 -1.20272574]]\n",
      "b1 = [[ 2.11530892]\n",
      " [ 3.41221357]\n",
      " [ 2.11585732]\n",
      " [-3.41221322]]\n",
      "W2 = [[-2512.9093032  -2502.70799785 -2512.01655969  2502.65264416]]\n",
      "b2 = [[-22.29071761]]\n"
     ]
    }
   ],
   "source": [
    "#测试nn_model\n",
    "print(\"=========================测试nn_model=========================\")\n",
    "X_assess, Y_assess = nn_model_test_case()\n",
    "\n",
    "parameters = nn_model(X_assess, Y_assess, 4, num_iterations=10000, print_cost=False)\n",
    "print(\"W1 = \" + str(parameters[\"W1\"]))\n",
    "print(\"b1 = \" + str(parameters[\"b1\"]))\n",
    "print(\"W2 = \" + str(parameters[\"W2\"]))\n",
    "print(\"b2 = \" + str(parameters[\"b2\"]))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 预测\n",
    "构建predict()来使用模型进行预测， 使用向前传播来预测结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(parameters,X):\n",
    "    \"\"\"\n",
    "    使用学习的参数，为X中的每个示例预测一个类\n",
    "    \n",
    "    参数：\n",
    "        parameters - 包含参数的字典类型的变量。\n",
    "        X - 输入数据（n_x，m）\n",
    "    \n",
    "    返回\n",
    "        predictions - 我们模型预测的向量（红色：0 /蓝色：1）\n",
    "     \n",
    "     \"\"\"\n",
    "    A2 , cache = forward_propagation(X,parameters)\n",
    "    predictions = np.round(A2)\n",
    "    \n",
    "    return predictions\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========================测试predict=========================\n",
      "预测的平均值 = 0.6666666666666666\n"
     ]
    }
   ],
   "source": [
    "#测试predict\n",
    "print(\"=========================测试predict=========================\")\n",
    "\n",
    "parameters, X_assess = predict_test_case()\n",
    "\n",
    "predictions = predict(parameters, X_assess)\n",
    "print(\"预测的平均值 = \" + str(np.mean(predictions)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 正式运行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "第  0  次循环，成本为：0.6930480201239823\n",
      "第  1000  次循环，成本为：0.3098018601352803\n",
      "第  2000  次循环，成本为：0.2924326333792646\n",
      "第  3000  次循环，成本为：0.2833492852647412\n",
      "第  4000  次循环，成本为：0.27678077562979253\n",
      "第  5000  次循环，成本为：0.26347155088593144\n",
      "第  6000  次循环，成本为：0.24204413129940763\n",
      "第  7000  次循环，成本为：0.23552486626608762\n",
      "第  8000  次循环，成本为：0.23140964509854278\n",
      "第  9000  次循环，成本为：0.22846408048352365\n",
      "准确率: 90%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "parameters = nn_model(X, Y, n_h = 4, num_iterations=10000, print_cost=True)\n",
    "\n",
    "#绘制边界\n",
    "plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n",
    "plt.title(\"Decision Boundary for hidden layer size \" + str(4))\n",
    "\n",
    "predictions = predict(parameters, X)\n",
    "print ('准确率: %d' % float((np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T)) / float(Y.size) * 100) + '%')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 更改隐藏层的节点数量\n",
    "现在我们更改隐藏层里面的节点数量，看一看节点数量是否会对结果造成影响。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "隐藏层的节点数量： 1  ，准确率: 67.25 %\n",
      "隐藏层的节点数量： 2  ，准确率: 66.5 %\n",
      "隐藏层的节点数量： 3  ，准确率: 89.25 %\n",
      "隐藏层的节点数量： 4  ，准确率: 90.0 %\n",
      "隐藏层的节点数量： 5  ，准确率: 89.75 %\n",
      "隐藏层的节点数量： 20  ，准确率: 90.0 %\n",
      "隐藏层的节点数量： 50  ，准确率: 89.75 %\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x2304 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 32))\n",
    "hidden_layer_sizes = [1, 2, 3, 4, 5, 20, 50] #隐藏层数量\n",
    "for i, n_h in enumerate(hidden_layer_sizes):\n",
    "    plt.subplot(5, 2, i + 1)\n",
    "    plt.title('Hidden Layer of size %d' % n_h)\n",
    "    parameters = nn_model(X, Y, n_h, num_iterations=5000)\n",
    "    plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n",
    "    predictions = predict(parameters, X)\n",
    "    accuracy = float((np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T)) / float(Y.size) * 100)\n",
    "    print (\"隐藏层的节点数量： {}  ，准确率: {} %\".format(n_h, accuracy))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 完整代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X的维度为: (2, 400)\n",
      "Y的维度为: (1, 400)\n",
      "数据集里面的数据有：400 个\n",
      "第  0  次循环，成本为：0.6930480201239823\n",
      "第  1000  次循环，成本为：0.3098018601352803\n",
      "第  2000  次循环，成本为：0.2924326333792646\n",
      "第  3000  次循环，成本为：0.2833492852647412\n",
      "第  4000  次循环，成本为：0.27678077562979253\n",
      "第  5000  次循环，成本为：0.26347155088593144\n",
      "第  6000  次循环，成本为：0.24204413129940763\n",
      "第  7000  次循环，成本为：0.23552486626608762\n",
      "第  8000  次循环，成本为：0.23140964509854278\n",
      "第  9000  次循环，成本为：0.22846408048352365\n",
      "准确率: 90%\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'\\nplt.figure(figsize=(16, 32))\\nhidden_layer_sizes = [1, 2, 3, 4, 5, 20, 50] #隐藏层数量\\nfor i, n_h in enumerate(hidden_layer_sizes):\\n    plt.subplot(5, 2, i + 1)\\n    plt.title(\\'Hidden Layer of size %d\\' % n_h)\\n    parameters = nn_model(X, Y, n_h, num_iterations=5000)\\n    plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\\n    predictions = predict(parameters, X)\\n    accuracy = float((np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T)) / float(Y.size) * 100)\\n    print (\"隐藏层的节点数量： {}  ，准确率: {} %\".format(n_h, accuracy))\\n'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "\"\"\"\n",
    "本文博客地址：https://blog.csdn.net/u013733326/article/details/79702148\n",
    "\n",
    "@author: Oscar\n",
    "\"\"\"\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from testCases import *\n",
    "import sklearn\n",
    "import sklearn.datasets\n",
    "import sklearn.linear_model\n",
    "from planar_utils import plot_decision_boundary, sigmoid, load_planar_dataset, load_extra_datasets\n",
    "\n",
    "%matplotlib inline \n",
    "#如果你使用用的是Jupyter Notebook的话请取消注释。\n",
    "\n",
    "np.random.seed(1) #设置一个固定的随机种子，以保证接下来的步骤中我们的结果是一致的。\n",
    "\n",
    "X, Y = load_planar_dataset()\n",
    "#plt.scatter(X[0, :], X[1, :], c=Y, s=40, cmap=plt.cm.Spectral) #绘制散点图\n",
    "shape_X = X.shape\n",
    "shape_Y = Y.shape\n",
    "m = Y.shape[1]  # 训练集里面的数量\n",
    "\n",
    "print (\"X的维度为: \" + str(shape_X))\n",
    "print (\"Y的维度为: \" + str(shape_Y))\n",
    "print (\"数据集里面的数据有：\" + str(m) + \" 个\")\n",
    "\n",
    "def layer_sizes(X , Y):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "     X - 输入数据集,维度为（输入的数量，训练/测试的数量）\n",
    "     Y - 标签，维度为（输出的数量，训练/测试数量）\n",
    "\n",
    "    返回：\n",
    "     n_x - 输入层的数量\n",
    "     n_h - 隐藏层的数量\n",
    "     n_y - 输出层的数量\n",
    "    \"\"\"\n",
    "    n_x = X.shape[0] #输入层\n",
    "    n_h = 4 #，隐藏层，硬编码为4\n",
    "    n_y = Y.shape[0] #输出层\n",
    "\n",
    "    return (n_x,n_h,n_y)\n",
    "\n",
    "def initialize_parameters( n_x , n_h ,n_y):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "        n_x - 输入节点的数量\n",
    "        n_h - 隐藏层节点的数量\n",
    "        n_y - 输出层节点的数量\n",
    "\n",
    "    返回：\n",
    "        parameters - 包含参数的字典：\n",
    "            W1 - 权重矩阵,维度为（n_h，n_x）\n",
    "            b1 - 偏向量，维度为（n_h，1）\n",
    "            W2 - 权重矩阵，维度为（n_y，n_h）\n",
    "            b2 - 偏向量，维度为（n_y，1）\n",
    "\n",
    "    \"\"\"\n",
    "    np.random.seed(2) #指定一个随机种子，以便你的输出与我们的一样。\n",
    "    W1 = np.random.randn(n_h,n_x) * 0.01\n",
    "    b1 = np.zeros(shape=(n_h, 1))\n",
    "    W2 = np.random.randn(n_y,n_h) * 0.01\n",
    "    b2 = np.zeros(shape=(n_y, 1))\n",
    "\n",
    "    #使用断言确保我的数据格式是正确的\n",
    "    assert(W1.shape == ( n_h , n_x ))\n",
    "    assert(b1.shape == ( n_h , 1 ))\n",
    "    assert(W2.shape == ( n_y , n_h ))\n",
    "    assert(b2.shape == ( n_y , 1 ))\n",
    "\n",
    "    parameters = {\"W1\" : W1,\n",
    "                  \"b1\" : b1,\n",
    "                  \"W2\" : W2,\n",
    "                  \"b2\" : b2 }\n",
    "\n",
    "    return parameters\n",
    "\n",
    "def forward_propagation( X , parameters ):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "         X - 维度为（n_x，m）的输入数据。\n",
    "         parameters - 初始化函数（initialize_parameters）的输出\n",
    "\n",
    "    返回：\n",
    "         A2 - 使用sigmoid()函数计算的第二次激活后的数值\n",
    "         cache - 包含“Z1”，“A1”，“Z2”和“A2”的字典类型变量\n",
    "     \"\"\"\n",
    "    W1 = parameters[\"W1\"]\n",
    "    b1 = parameters[\"b1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "    b2 = parameters[\"b2\"]\n",
    "    #前向传播计算A2\n",
    "    Z1 = np.dot(W1 , X) + b1\n",
    "    A1 = np.tanh(Z1)\n",
    "    Z2 = np.dot(W2 , A1) + b2\n",
    "    A2 = sigmoid(Z2)\n",
    "    #使用断言确保我的数据格式是正确的\n",
    "    assert(A2.shape == (1,X.shape[1]))\n",
    "    cache = {\"Z1\": Z1,\n",
    "             \"A1\": A1,\n",
    "             \"Z2\": Z2,\n",
    "             \"A2\": A2}\n",
    "\n",
    "    return (A2, cache)\n",
    "\n",
    "def compute_cost(A2,Y,parameters):\n",
    "    \"\"\"\n",
    "    计算方程（6）中给出的交叉熵成本，\n",
    "\n",
    "    参数：\n",
    "         A2 - 使用sigmoid()函数计算的第二次激活后的数值\n",
    "         Y - \"True\"标签向量,维度为（1，数量）\n",
    "         parameters - 一个包含W1，B1，W2和B2的字典类型的变量\n",
    "\n",
    "    返回：\n",
    "         成本 - 交叉熵成本给出方程（13）\n",
    "    \"\"\"\n",
    "\n",
    "    m = Y.shape[1]\n",
    "    W1 = parameters[\"W1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "\n",
    "    #计算成本\n",
    "    logprobs = logprobs = np.multiply(np.log(A2), Y) + np.multiply((1 - Y), np.log(1 - A2))\n",
    "    cost = - np.sum(logprobs) / m\n",
    "    cost = float(np.squeeze(cost))\n",
    "\n",
    "    assert(isinstance(cost,float))\n",
    "\n",
    "    return cost\n",
    "\n",
    "def backward_propagation(parameters,cache,X,Y):\n",
    "    \"\"\"\n",
    "    使用上述说明搭建反向传播函数。\n",
    "\n",
    "    参数：\n",
    "     parameters - 包含我们的参数的一个字典类型的变量。\n",
    "     cache - 包含“Z1”，“A1”，“Z2”和“A2”的字典类型的变量。\n",
    "     X - 输入数据，维度为（2，数量）\n",
    "     Y - “True”标签，维度为（1，数量）\n",
    "\n",
    "    返回：\n",
    "     grads - 包含W和b的导数一个字典类型的变量。\n",
    "    \"\"\"\n",
    "    m = X.shape[1]\n",
    "\n",
    "    W1 = parameters[\"W1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "\n",
    "    A1 = cache[\"A1\"]\n",
    "    A2 = cache[\"A2\"]\n",
    "\n",
    "    dZ2= A2 - Y\n",
    "    dW2 = (1 / m) * np.dot(dZ2, A1.T)\n",
    "    db2 = (1 / m) * np.sum(dZ2, axis=1, keepdims=True)\n",
    "    dZ1 = np.multiply(np.dot(W2.T, dZ2), 1 - np.power(A1, 2))\n",
    "    dW1 = (1 / m) * np.dot(dZ1, X.T)\n",
    "    db1 = (1 / m) * np.sum(dZ1, axis=1, keepdims=True)\n",
    "    grads = {\"dW1\": dW1,\n",
    "             \"db1\": db1,\n",
    "             \"dW2\": dW2,\n",
    "             \"db2\": db2 }\n",
    "\n",
    "    return grads\n",
    "\n",
    "def update_parameters(parameters,grads,learning_rate=1.2):\n",
    "    \"\"\"\n",
    "    使用上面给出的梯度下降更新规则更新参数\n",
    "\n",
    "    参数：\n",
    "     parameters - 包含参数的字典类型的变量。\n",
    "     grads - 包含导数值的字典类型的变量。\n",
    "     learning_rate - 学习速率\n",
    "\n",
    "    返回：\n",
    "     parameters - 包含更新参数的字典类型的变量。\n",
    "    \"\"\"\n",
    "    W1,W2 = parameters[\"W1\"],parameters[\"W2\"]\n",
    "    b1,b2 = parameters[\"b1\"],parameters[\"b2\"]\n",
    "\n",
    "    dW1,dW2 = grads[\"dW1\"],grads[\"dW2\"]\n",
    "    db1,db2 = grads[\"db1\"],grads[\"db2\"]\n",
    "\n",
    "    W1 = W1 - learning_rate * dW1\n",
    "    b1 = b1 - learning_rate * db1\n",
    "    W2 = W2 - learning_rate * dW2\n",
    "    b2 = b2 - learning_rate * db2\n",
    "\n",
    "    parameters = {\"W1\": W1,\n",
    "                  \"b1\": b1,\n",
    "                  \"W2\": W2,\n",
    "                  \"b2\": b2}\n",
    "\n",
    "    return parameters\n",
    "\n",
    "def nn_model(X,Y,n_h,num_iterations,print_cost=False):\n",
    "    \"\"\"\n",
    "    参数：\n",
    "        X - 数据集,维度为（2，示例数）\n",
    "        Y - 标签，维度为（1，示例数）\n",
    "        n_h - 隐藏层的数量\n",
    "        num_iterations - 梯度下降循环中的迭代次数\n",
    "        print_cost - 如果为True，则每1000次迭代打印一次成本数值\n",
    "\n",
    "    返回：\n",
    "        parameters - 模型学习的参数，它们可以用来进行预测。\n",
    "     \"\"\"\n",
    "\n",
    "    np.random.seed(3) #指定随机种子\n",
    "    n_x = layer_sizes(X, Y)[0]\n",
    "    n_y = layer_sizes(X, Y)[2]\n",
    "\n",
    "    parameters = initialize_parameters(n_x,n_h,n_y)\n",
    "    W1 = parameters[\"W1\"]\n",
    "    b1 = parameters[\"b1\"]\n",
    "    W2 = parameters[\"W2\"]\n",
    "    b2 = parameters[\"b2\"]\n",
    "\n",
    "    for i in range(num_iterations):\n",
    "        A2 , cache = forward_propagation(X,parameters)\n",
    "        cost = compute_cost(A2,Y,parameters)\n",
    "        grads = backward_propagation(parameters,cache,X,Y)\n",
    "        parameters = update_parameters(parameters,grads,learning_rate = 0.5)\n",
    "\n",
    "        if print_cost:\n",
    "            if i%1000 == 0:\n",
    "                print(\"第 \",i,\" 次循环，成本为：\"+str(cost))\n",
    "    return parameters\n",
    "\n",
    "def predict(parameters,X):\n",
    "    \"\"\"\n",
    "    使用学习的参数，为X中的每个示例预测一个类\n",
    "\n",
    "    参数：\n",
    "        parameters - 包含参数的字典类型的变量。\n",
    "        X - 输入数据（n_x，m）\n",
    "\n",
    "    返回\n",
    "        predictions - 我们模型预测的向量（红色：0 /蓝色：1）\n",
    "\n",
    "     \"\"\"\n",
    "    A2 , cache = forward_propagation(X,parameters)\n",
    "    predictions = np.round(A2)\n",
    "\n",
    "    return predictions\n",
    "\n",
    "parameters = nn_model(X, Y, n_h = 4, num_iterations=10000, print_cost=True)\n",
    "\n",
    "#绘制边界\n",
    "plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n",
    "plt.title(\"Decision Boundary for hidden layer size \" + str(4))\n",
    "\n",
    "predictions = predict(parameters, X)\n",
    "print ('准确率: %d' % float((np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T)) / float(Y.size) * 100) + '%')\n",
    "\n",
    "\"\"\"\n",
    "plt.figure(figsize=(16, 32))\n",
    "hidden_layer_sizes = [1, 2, 3, 4, 5, 20, 50] #隐藏层数量\n",
    "for i, n_h in enumerate(hidden_layer_sizes):\n",
    "    plt.subplot(5, 2, i + 1)\n",
    "    plt.title('Hidden Layer of size %d' % n_h)\n",
    "    parameters = nn_model(X, Y, n_h, num_iterations=5000)\n",
    "    plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n",
    "    predictions = predict(parameters, X)\n",
    "    accuracy = float((np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T)) / float(Y.size) * 100)\n",
    "    print (\"隐藏层的节点数量： {}  ，准确率: {} %\".format(n_h, accuracy))\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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